JP6552546B2 - Information providing apparatus, information providing method, and information providing apparatus program - Google Patents

Description

  Embodiments of the present invention relate to an information providing device, an information providing method, and an information providing device program.

  Conventionally, genetic information obtained by genetic testing has come to be utilized in various fields. For example, Patent Literature 1 discloses a method for utilizing genetic test data that can be suitably used by life insurance companies, pharmaceutical companies, food companies, and the like.

JP 2001-256305 A

  However, in the above-described conventional technology, it is not always possible to provide more suitable information to the target person using the user behavior information and genetic information. For example, in the above-mentioned prior art, a gene information file in which genetic information obtained by genetic testing and medical history information of a subject are associated is created and provided to a medical, pharmaceutical, food development or manufacturing organization Do. In addition, the institution that has received the provision of the gene information file provides the individual with information (for example, medicine, food, etc.) based on the gene information file.

  As described above, since the above-described conventional techniques only provide information based on the genetic information and the medical history information of the subject, it is not always necessary for the target person to use the user's behavioral information and the genetic information. It is not always possible to provide more appropriate information.

  The present application has been made in view of the above, and an object thereof is to provide an information providing apparatus capable of providing more appropriate information to a target person using user behavior information and genetic information. I assume.

  An information providing apparatus according to the present invention is a target person having behavior information indicating behavior of a user on a network, an acquisition unit for acquiring gene information of the user, and behavior information related to the behavior information of the user. And providing means for providing information based on the gene information of the user.

  According to one aspect of the embodiment, it is possible to provide information more suitable for the subject by using the user's behavior information and the gene information.

FIG. 1 is a diagram illustrating an example of a providing process according to the embodiment. FIG. 2 is a diagram showing an example of the configuration of the information providing system according to the embodiment. FIG. 3 is a diagram illustrating an exemplary configuration of the information providing apparatus according to the embodiment. FIG. 4 is a diagram showing an example of the gene information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a purchase history storage unit according to the embodiment. FIG. 6 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 7 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 8 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. FIG. 9 is a flowchart showing the overall flow of the providing process by the information providing apparatus according to the embodiment. FIG. 10 is a diagram illustrating an example of a search history storage unit according to the embodiment. FIG. 11 is a diagram illustrating an example of a browsing history storage unit according to the embodiment. FIG. 12 is a hardware configuration diagram showing an example of a computer for realizing the function of the information providing device.

  Hereinafter, an information providing apparatus, an information providing method, and a mode for implementing an information providing apparatus program according to the present application (hereinafter, referred to as an “embodiment”) will be described with reference to the drawings. Note that the information providing apparatus, the information providing method, and the information providing apparatus program according to the present application are not limited by this embodiment. Moreover, in the following embodiments, the same reference numerals are given to the same parts, and the overlapping description will be omitted.

[1. Provision processing)
First, an example of the providing process according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of a providing process according to the embodiment. The providing process according to the embodiment is performed by the information providing apparatus 100 illustrated in FIG.

  Further, as shown in FIG. 1, the information providing system 1 according to the embodiment includes a user terminal 10 and an information providing apparatus 100. The user terminal 10 and the information providing apparatus 100 are communicably connected by wire or wireless via a network. The information providing system 1 shown in FIG. 1 may include a plurality of user terminals 10 and a plurality of information providing apparatuses 100. Although described later, the information providing system 1 also includes a vendor terminal 30 and an external server 60.

  The user terminal 10 is a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. For example, the user terminal 10 displays information received from the information providing apparatus 100 on a screen or outputs a voice.

  Here, the premise of this embodiment is demonstrated. For example, the relationship between the purchase behavior of the user on the network (for example, an action such as buying a product as a site) and the search action (for example, an action such as information search using a certain search keyword) There is a data analysis method (also referred to as "quality expansion search" or "quality expansion search") in which a user who is not performing purchasing behavior searches what kind of purchasing behavior.

  “Quality expansion search” will be described in more detail using an example. For example, a user who performs purchasing behavior such as “buy liquor” tends to search for information using the search keyword “beer”. Do. In such a case, if an unknown subject among the subjects whose purchase behavior is unknown performs an information search using the search keyword “beer”, this unknown subject may also “buy sake”. Predict that there is. In this way, “quality extended search” is a user who is predicted to take a certain action from a group of users using a plurality of types of information (in this example, there is a possibility of “buying alcohol”). It effectively searches for a certain user.

  We will explain yet another premise. For example, a person who suffers from a particular disease may be subjected to a genetic test to conduct a clinical test to identify the type of gene associated with the disease (eg, the cause of the disease). However, for example, if this disease is a very rare disease, the test results of the clinical test may not necessarily be accurate because there are few subjects. Moreover, when the onset of the disease is caused by a combination of a plurality of genes, it is difficult to specify the combination of the plurality of genes in the clinical examination. Therefore, for example, a relationship between a disease predicted from the user's behavior and a gene is searched, and when a relationship is obtained between a certain disease and a certain gene, this gene is determined as a causative factor of the disease. And it is thought that the accuracy of gene identification caused by a disease can be enhanced by comparing this judgment result with the test result of the clinical test. Also, for example, it is considered that scientific report content can be reinforced.

  The providing process performed by the information providing apparatus 100 according to the embodiment pays attention to such “quality extended search” and provides information by applying the gene information of the user to “quality extended search”. Specifically, the information providing apparatus 100 according to the embodiment acquires behavior information indicating behavior on a user's network and genetic information of the user. Then, the information providing apparatus 100 provides information based on the user's gene information to the subject having the action information related to the user's action information.

  As described above, in this embodiment, “quality-enhanced search” using genetic information means that a target person who has behavior information related to user behavior information can perform genetic information similar to that user. It is to search out as a person with sex. More specifically, “quality-enhanced search” using genetic information refers to a relationship between behavioral information and genetic information that a user who performs a specific behavior tends to have a specific gene. Among the subjects who have not received a genetic test and whose genetic information is unknown, for example, a subject having behavioral information related to this behavioral information is a genetic information similar to the user. Predict as a person who may

  In addition, the information providing apparatus 100 according to the embodiment identifies genes associated with diseases using behavioral information and gene information, and reinforces the test results of conventionally used tests and scientific report contents on genes. It is Hereinafter, the providing process according to the embodiment will be described using an example.

  First, the information providing apparatus 100 acquires behavior information indicating behavior of the user on the network and gene information of the user (Step S1). The genetic information is a test result obtained by genetic test, and is, for example, a list of genes possessed by the user. Also, genetic information is information indicating what type (genotype) a gene related to the onset of a specific disease is. For example, a gene related to the onset of “cancer” is referred to as “GINE1” for convenience of explanation. And if the type of "GINE1" is "a" type and it is known that the incidence rate of "cancer" is particularly high, the user can use genetic testing to determine that his "GINE1" is You can know whether it is “a” type or not.

  The information providing apparatus 100 acquires such gene information from the testing laboratory that has performed the gene test. For example, the information providing apparatus 100 acquires gene information by accessing a server device (examination institution server) belonging to the examination institution. In addition, a management company (hereinafter referred to as “management company T”) that manages the information providing apparatus 100 has a predetermined contract with such a testing organization, and the user who received the genetic test gets approval. Such acquisition of genetic information is possible when it is The information providing apparatus 100 may directly receive provision of gene information from a user who has received a genetic test. That is, it is not limited how the information providing apparatus 100 acquires the gene information.

  In addition, the information providing apparatus 100 stores the acquired gene information in the gene information storage unit 121 which is a storage unit in the own apparatus. The gene information storage unit 121 is a storage unit for storing gene information obtained by genetic testing, and as shown in FIG. 1, identification information (user ID) for identifying each user who has undergone genetic testing, and The user's genetic information is stored in association with each other.

  That is, the gene information storage unit 121 stores, as gene information, what type of gene each user has. For example, the gene information storage unit 121 stores what type of gene each user has among the genes having a plurality of types by having SNP (Single Nucleotide Polymorphism) as gene information. Further, the gene information storage unit 121 stores, as gene information, what type of gene each user has in a gene involved in the onset of a disease.

  For example, in the gene information storage unit 121 illustrated in FIG. 1, the gene information of the user U1 indicates that the user U1 has the genes “G1a”, “G2a”, “G3a”, “G4a”,. . Here, it is assumed that the lower case alphabet given to the gene mark in the present embodiment indicates the type of gene. For example, the gene "G1a" indicates the gene "G1" of the "a" type. That is, it is indicated that the user U1 has the “a” type gene “G1” in the gene “G1” in which a plurality of types exist by SNP. Similarly, in the example of FIG. 1, the user U2 is shown to have the “b” type gene “G1” in the gene “G1” in which a plurality of types exist.

  In addition, the information providing apparatus 100 acquires purchase information, which is information related to the purchase made by the user, as the action information of the user. The purchase information is information indicating purchase behavior such as which user purchased what when. That is, purchase information can be paraphrased as purchase history. For example, the information providing apparatus 100 acquires purchase information from a predetermined server device (for example, a shopping server). Then, the information providing device 100 stores the acquired purchase information in the purchase history storage unit 122 which is a storage unit in the own device.

  As shown in FIG. 1, the purchase history storage unit 122 stores identification information (user ID) for identifying each user in association with the purchase information of the user. That is, in the example of FIG. 1, the purchase history storage unit 122 stores purchase information such as what each user has purchased. The example of FIG. 1 shows an example in which the user U1 performs a purchasing action such as "Buy laptop PC P1". Note that the information providing apparatus 100 may acquire purchase information at an arbitrary timing. For example, the information providing apparatus 100 periodically acquires purchase information.

  Further, each piece of gene information stored in the gene information storage unit 121 and the action information stored in the purchase history storage unit 122 are associated with each other by a common user ID. In the example of FIG. 1, the gene information associated with the user ID “U1” and the purchase information associated with the user ID “U1” are linked by the user ID “U1”. Further, such a user ID is account information uniquely issued when the user performs member registration with the management company T.

  Next, the information providing apparatus 100 analyzes the relationship between the purchase information acquired in step S1 and the gene information (step S2). Specifically, the information providing apparatus 100 analyzes whether a predetermined relationship is established between the behavior information and the gene information. For example, the information providing apparatus 100 analyzes, as the predetermined relationship, whether or not the relationship based on the tendency of the behavior information and the gene information is established. The relationship based on the tendency indicates a correlation.

  More specifically, the information providing apparatus 100 analyzes whether or not a correlation is established between each behavior information and each gene information by performing a correlation analysis between each behavior information and each gene information. . As an example, in the information providing apparatus 100, a user who performs purchasing behavior such as "buy notebook PC P1" tends to have the gene "G1a", that is, purchasing behavior "buy notebook PC P1" and gene information An analysis is made as to whether a correlation is established with "G1a". A specific analysis method will be described later.

  Next, the information providing apparatus 100 specifies behavior information and gene information that are correlated from the result of the correlation analysis (step S3). For example, when there is a gene that is correlated with the purchase behavior such as “buy notebook PC P1”, the information providing apparatus 100 is the gene stored in the gene information storage unit 121. Identify if there is. In this example, it is assumed that the information providing apparatus 100 specifies that the purchasing behavior “buy sake P3” and the gene “G2b” are correlated. In other words, it is assumed that the information providing apparatus 100 identifies a tendency showing a correlation that the user "buy sake P3" tends to have the gene "G2b".

  In addition, the constitution which a gene "G2" gives to a user is related as a factor which such a tendency is acquired. For example, the gene “G2” is a gene involved in the enzyme activity of the alcohol metabolizing enzyme, and the alcohol metabolizing enzyme based on the “b” type gene “G2b” has a stronger enzyme activity. In such a case, the user having the gene "G2b" has a constitution of "strong in alcohol", and as a result, it leads to a tendency that he likes alcohol and it becomes easy to buy alcohol. In addition, although the constitution was taken as an example here, the same thing can be said to a disease. As an example, for a user who has a gene that causes the onset of a particular disease, the tendency is that it is easier to perform purchasing behavior related to the disease (for example, buying medicines for the disease) or search behavior (examining the disease). Lead to

  Therefore, the information processing apparatus 100 predicts not only the behavior information but also the correlation between the prediction information predicted from the behavior information (for example, constitution and disease) and the genetic information. It is also possible to make recommendations based on information.

  Next, in step S3, if there is a target person who has behavior information related to (for example, the same or similar to) the behavior information obtained from the relationship with the genetic information in step S3, the information providing apparatus 100 Are also predicted to have genetic information associated with such behavior information (step S4). For example, as described above, the information providing apparatus 100 performs a purchasing action of “buy sake P3” when it is identified that the buying action “buy sake P3” and the gene “G2b” are correlated. The subject is predicted to have the gene “G2b”. Then, the information providing apparatus 100 provides the subject with information based on the gene “G2b”. Here, a process in which the information providing apparatus 100 extracts the target person having the purchasing behavior “buy sake P3” will be described.

  For example, since the information providing apparatus 100 is registered as a member at the management company T, among users who have an account with the management company T, the information provision apparatus 100 has performed purchasing behavior such as "buy sake P3". The user is extracted from the purchase history storage unit 122. Next, the information providing apparatus 100 extracts, from among the extracted users, a user having no gene information, that is, a user who does not know what gene it has as a target person. Here, it is assumed that the information providing apparatus 100 has extracted the user Ux.

  Therefore, the information providing apparatus 100 predicts that the user Ux extracted as the target person also has the gene “G2b”. Therefore, the information providing apparatus 100 provides information based on the gene information “G2b” to the user Ux (step S5). For example, when the genetic information “G2b” is a causal factor of a specific constitution, the information providing apparatus 100 makes a recommendation or alert for the constitution. For example, as described above, when the gene “G2b” is a factor that produces a constitution that is strong against alcohol, the information providing apparatus 100 performs “drinking precautions” or “non-alcoholic beverage proposal”. In addition, when the genetic information “G2b” is a causative factor of a specific disease, the information providing device 100 may recommend or warn about the disease.

  Now, as described above, the information providing apparatus 100 according to the embodiment acquires behavior information indicating a behavior of the user on the network and gene information of the user. And the information provision apparatus 100 provides the information based on a user's genetic information with respect to the subject who has the behavior information relevant to a user's behavior information.

  As described above, the information processing apparatus 100 can provide more appropriate information to the target person by using the behavior information and gene information of the user. For example, the information processing apparatus 100 can predict what kind of gene a target person who can not obtain gene information has, by using the behavior information of the user and the gene information. For this reason, since the information processing apparatus 100 can provide information on a constitution or a disease that causes the gene as information based on the gene to the subject, for example, for constitution improvement or disease prevention. Can contribute.

[2. System configuration)
Next, the configuration of the information providing system according to the embodiment will be described with reference to FIG. FIG. 2 is a diagram showing an example of the configuration of the information providing system 1 according to the embodiment. As shown in FIG. 2, the information providing system 1 includes a user terminal 10, an inspection organization server 30, an external server 60, and an information providing apparatus 100. The user terminal 10, the inspection organization server 30, the external server 60, and the information providing apparatus 100 are connected via a network N so as to be communicable by wire or wirelessly.

  Although omitted in FIG. 1, the information providing system 1 according to the embodiment further includes an inspection agency server 30 and an external server 60 as shown in FIG. 2. The inspection organization server 30 is a server device belonging to a predetermined inspection organization which conducts genetic examination, and accumulates genetic information which is the examination result. For example, in response to a request from the information providing device 100, the inspection agency server 30 transmits gene information to the information providing device 100.

  The external server 60 is a server device that is the source of various action information. For example, the external server 60 is a shopping server that provides an EC (Electronic Commerce) site such as a shopping site or an electronic mall. The shopping server stores purchase information (an example of action information) which is information related to the purchase made by the user.

  Also, for example, the external server 60 is a search server that provides a search service. The search server stores search behavior information (an example of behavior information) which is information on a search performed by a user using a search keyword.

  Also, for example, the external server 60 is a content server that distributes web pages including advertisement content and article content. The content server accumulates advertisement browsing information (an example of behavior information) which is information on browsing behavior in which the user browses the advertisement content. In addition, the content server stores article browsing information (an example of behavior information) which is information on the browsing behavior in which the user browses the article content.

  For example, the external server 60 is a stock transaction management server that provides content related to stock transactions. The stock transaction management server stores stock transaction information (an example of action information) which is information on stock transactions made by the user.

[3. Configuration of Information Providing Device]
Next, the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram showing an example of the configuration of the information providing apparatus 100 according to the embodiment. As shown in FIG. 3, the information providing apparatus 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

(About the communication unit 110)
The communication unit 110 is realized by, for example, a network interface card (NIC). The communication unit 110 is connected to the network N by wire or wirelessly, and transmits / receives information to / from the user terminal 10, the inspection organization server 30, and the external server 60, for example.

  The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 120 includes a gene information storage unit 121 and a purchase history storage unit 122. Although not shown, the storage unit 120 further includes a storage unit in which the information provided by the providing unit 134 is stored. As an example of this, the storage unit 120 includes an advertisement content storage unit that stores advertisement content.

(About the gene information storage unit 121)
The gene information storage unit 121 is a storage unit that stores gene information obtained by genetic testing. Also, the gene information stored in the gene information storage unit 121 is acquired by the acquisition unit 131. Here, FIG. 4 illustrates an example of the gene information storage unit 121 according to the embodiment. In the example of FIG. 4, the gene information storage unit 121 has items such as “user ID”, “gene information”, “name”, “address”, and “birth date”.

  "User ID" indicates identification information for identifying a user. Although explained also in FIG. 1, “genetic information” indicates genetic information based on an analysis result obtained by analyzing a user's gene by genetic test. Specifically, genetic information is information such as what type of gene each user has among genes having a plurality of types by having a SNP. Moreover, genetic information is information such as what type of gene each user has in genes involved in the onset of a disease.

  “Name” indicates the name of the user. “Address” indicates the address of the user. "Date of birth" indicates the date of birth of the user. The “name”, “address”, and “date of birth” are, for example, input by the user when applying for genetic testing.

  That is, in the example of FIG. 4, the user U1 has the gene “G1a” that is the gene “G1” of the “a” type among the genes “G1” having a plurality of types by SNP. Similarly, in the example of FIG. 1, the user U2 indicates that the gene “G1b” that is the gene “G1” of the “b” type among the genes “G1” having a plurality of types exists. As shown in FIG. 4, each gene information stored in the gene information storage unit 121 is assigned a code for identifying each gene information. For example, the gene information corresponding to the user U1 is given the code "rd11". Hereinafter, such gene information is referred to as “gene information rd11”. The same applies to other gene information.

(About the purchase history storage unit 122)
The purchase history storage unit 122 is a storage unit that stores a history of purchase information (an example of action information) which is information related to a purchase made by the user, that is, a purchase history. The purchase history storage unit 122 stores information such as when and what each user has purchased as purchase information. The purchase information stored in the purchase history storage unit 122 is acquired by the acquisition unit 131. Here, FIG. 5 shows an example of the purchase history storage unit 122 according to the embodiment. In the example of FIG. 5, the purchase history storage unit 122 includes items such as “user ID”, “purchased product”, and “purchase date / time”.

  "User ID" indicates identification information for identifying a user. The gene information stored in the gene information storage unit 121 and the purchase information stored in the purchase history storage unit 122 are linked with the same user ID. That is, gene information and purchase information to which the same "user ID" is associated are obtained from the same user. “Purchased product” indicates a product purchased by the corresponding user. “Purchasing date” indicates the date and time when the “purchased product” was purchased by the corresponding user.

  That is, in the example of FIG. 5, an example is shown in which the user U1 performs the purchasing action of “buy notebook PC P1” on “Jan. 10, 2017”. As shown in FIG. 5, the purchase information stored in the purchase history storage unit 122 is assigned a code for identifying each purchase information. For example, the purchase information corresponding to the user U1 is given the code "pd11". Hereinafter, such purchase information is referred to as “purchase information pd11”. The same applies to other purchase information.

(Control unit 130)
Returning to FIG. 3, the control unit 130 executes various programs stored in a storage device inside the information providing apparatus 100 by using a RAM as a work area by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Is realized. Further, the control unit 130 is realized by, for example, an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  As shown in FIG. 3, the control unit 130 includes an acquisition unit 131, an analysis unit 132, a specification unit 133, and a provision unit 134, and implements or executes the function or action of the information processing described below. . Note that the internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 3, and may be another configuration as long as the information processing described below is performed. Moreover, the connection relation of each processing unit included in the control unit 130 is not limited to the connection relation illustrated in FIG. 2, and may be another connection relation.

(About acquisition unit 131)
The acquisition unit 131 acquires behavior information indicating behavior of the user on the network and gene information of the user. For example, the acquisition unit 131 acquires genetic information from a laboratory that has performed a genetic test. For example, the acquisition unit 131 acquires gene information by accessing the inspection engine server 30, which is a server device belonging to the inspection authority. For example, the acquisition unit 131 periodically accesses the examination institution server 30 to acquire gene information. In addition, the acquisition unit 131 stores the acquired gene information in the gene information storage unit 121 as shown in FIG. 4.

  Also, for example, the acquisition unit 131 acquires, as the action information of the user, purchase information that is information related to the purchase made by the user. For example, the acquisition unit 131 acquires purchase information by accessing the external server 60 (for example, a shopping server). For example, the acquisition unit 131 periodically accesses the external server 60 to acquire purchase information. In addition, the acquisition unit 131 stores the acquired purchase information in the purchase history storage unit 122 as shown in FIG.

(About the analysis unit 132)
The analysis unit 132 analyzes the relationship between the behavior information and the gene information acquired by the acquisition unit 131. Specifically, the analysis unit 132 analyzes whether or not a predetermined relationship is established between the behavior information and the gene information. For example, the analysis unit 132 analyzes whether the relationship based on the tendency between the behavior information and the gene information is established as the predetermined relationship. In the present embodiment, the analysis unit 132 analyzes whether or not a correlation is established between the behavior information and the gene information.

  For example, when the purchase information is acquired by the acquisition unit 131, the analysis unit 132 analyzes the relationship between the purchase information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between purchase information and gene information. The following three patterns can be considered as an analysis method. Below, each pattern is demonstrated using purchase information as an example of action information.

(Pattern 1)
First, the pattern 1 will be described with reference to FIG. FIG. 6 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. In pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each piece of action information and each piece of gene information by performing a correlation analysis between each piece of action information and each piece of gene information. First, the analysis unit 132 refers to the gene information storage unit 121 and lists up users having the gene for each gene. Specifically, as shown in FIG. 6A, the analysis unit 132 gives “1” to the user who has the gene for each gene contained in the gene information, and has the gene for each gene. Assign "0" to non-users. For example, in the example of the gene information storage unit 121 illustrated in FIG. 4, it can be seen from the gene information rd11 that the user U1 has the gene “G1a”. Therefore, as shown in FIG. 6A, the analysis unit 132 assigns “1” to the input field corresponding to the gene “G1a” and the user ID “U1”. Then, the analysis unit 132 generates a gene-user list as shown in FIG. 6 (a).

  Further, the analysis unit 132 refers to the purchase history storage unit 122, and lists up the users who have purchased each product during the period Tn (according to the time series). Here, the period T1 is set to "one month", and this one month is further set as "January 1 2017-January 31 17". In such a state, as shown in FIG. 6 (b), the analysis unit 132 is performed during “January 1 2017 to January 31 17” in the acquired purchase information. For each product included in the purchase information related to the purchase, “1” is given to the user who purchased the product, and “0” is given to the user who has not purchased the product for each product. For example, in the example of the purchase history storage unit 122 shown in FIG. 5, it can be understood from the purchase information pd11 that the user U1 has purchased the “notebook computer P1” on “Jan. 10, 2017”. Therefore, as shown in FIG. 6B, the analysis unit 132 assigns “1” to the input field corresponding to “notebook personal computer P1” and user ID “U1”. Then, the analysis unit 132 generates a product (notebook computer P1) -user list as shown in FIG. 6B.

  Also, similarly, the analysis unit 132 is included in the purchase information related to the purchase performed during “February 1, 2017 to February 29, 2017” (period T2) among the acquired purchase information. A product-user list is generated by assigning “1” to a user who purchases the product for each product and assigning “0” to a user who has not purchased the product for each product. . That is, the analysis unit 132 generates a product (notebook computer P1) -user list every period Tn. In addition, although the notebook computer P1 has been described as an example, the analysis unit 132 is, as shown in FIG. 6B, a product-user list for each period Tn for each product, such as a suit P2 and a sake P3. Generate

  Hereinafter, an example of correlation analysis with purchasing behavior "buy notebook PC P1" and gene information "G1a" is explained. First, let the variable X be the number of users who purchased the “notebook computer P1” in the period Tn. Further, the variable Y is the number of users who have the gene “G1a” among the number of users who purchased “notebook personal computer P1” during the period Tn. In such a state, as shown in FIG. 6C, the analysis unit 132 counts the variable X and the variable Y for each period Tn corresponding to the time series. For example, the analysis unit 132 determines the number of users who purchased the “notebook computer P1” in “January 1, 2017 to January 31, 2017” (period T1), and the gene “G1a” of the number of users. Count the number of users who have Similarly, the analysis unit 132 counts for each period Tn. Here, it is assumed that the analysis unit 132 has obtained the count result as shown in FIG.

  Based on the count result, the analysis unit 132 determines whether a user who performs purchasing behavior such as "buy notebook PC P1" tends to have the gene "G1a", that is, purchasing behavior "buy notebook PC P1" and It is analyzed whether a correlation is established with the information “G1a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. Then, if the calculated correlation coefficient is, for example, a predetermined value or more, the analysis unit 132 indicates that the correlation between the purchasing behavior “buy notebook PC P1” and the gene information “G1a” is established. Obtain analysis results. On the other hand, if the calculated correlation coefficient is equal to or less than a predetermined value, the analysis unit 132 obtains a correlation analysis result that the purchasing behavior “buy notebook PC P1” and the gene information “G1a” are not correlated.

  In FIG. 6, the purchasing behavior “buy notebook PC P1” and the gene information “G1a” are described as an example, but the analysis unit 132 corresponds to each product (for example, suit P2, sake P3 etc.) The correlation between purchase information and gene information (for example, G1b, G2a, etc.) corresponding to each gene is analyzed to calculate a correlation coefficient.

(Pattern 2)
Next, pattern 2 will be described with reference to FIG. FIG. 7 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. In pattern 2, the analysis unit 132 performs correlation analysis between each piece of action information and a combination of a plurality of pieces of gene information among the acquired pieces of gene information to obtain a combination of each piece of action information and a plurality of pieces of gene information. Analyze whether correlation is established. First, the analysis unit 132 refers to the gene information storage unit 121 and lists a user having the gene for each combination of a plurality of genes. For example, when there are “300,000” candidate genes, there are “300,000 × 300,000” combinations of a plurality of genes. Specifically, as shown in FIG. 7A, the analysis unit 132 gives “1” to the user having the combination of a plurality of genes for each combination of a plurality of genes, and "0" is given to the user who does not have the combination of the gene concerned. For example, in the example of the gene information storage unit 121 illustrated in FIG. 4, it is understood from the gene information rd11 that the user U1 has a combination of the genes “G1a” and “G2a”. Therefore, as shown in FIG. 7A, the analysis unit 132 assigns “1” to the input field corresponding to such a combination. Then, the analysis unit 132 generates a gene combination-user list as shown in FIG. 7 (a). Here, in order to simplify the explanation, the combination of a plurality of genes is a combination of two genes, but the number of genes to be combined is not limited.

  Further, the analysis unit 132 refers to the purchase history storage unit 122, and lists up users who have purchased each product during a period Tn (a period corresponding to a time series). Here, the period T1 is set to "one month", and this one month is further set as "January 1 2017-January 31 17". In such a state, as shown in FIG. 7B, the analysis unit 132 was performed between “January 1, 2017 to January 31, 2017” in the acquired purchase information. For each product included in the purchase information related to the purchase, “1” is given to the user who purchased the product, and “0” is given to the user who has not purchased the product for each product. For example, in the example of the purchase history storage unit 122 shown in FIG. 5, it can be understood from the purchase information pd11 that the user U1 has purchased the “notebook computer P1” on “Jan. 10, 2017”. Therefore, as shown in FIG. 7B, the analysis unit 132 assigns “1” to the input field corresponding to “notebook personal computer P1” and user ID “U1”. Then, the analysis unit 132 generates a product (notebook computer P1) -user list as shown in FIG. 7B.

  Also, similarly, the analysis unit 132 is included in the purchase information related to the purchase performed during “February 1, 2017 to February 29, 2017” (period T2) among the acquired purchase information. A product-user list is generated by assigning “1” to a user who purchases the product for each product and assigning “0” to a user who has not purchased the product for each product. . That is, the analysis unit 132 generates a product (notebook computer P1) -user list every period Tn. In addition, although the notebook computer P1 has been described as an example, the analysis unit 132 is, as shown in FIG. 7B, a product-user list for each period Tn for each product, such as a suit P2 and a sake P3. Generate

  Hereinafter, an example of a correlation analysis between the purchase behavior “buy notebook PC P1” and the gene combination “G1a-G2a” will be described. First, let the variable X be the number of users who purchased the “notebook computer P1” in the period Tn. Further, among the number of users who purchased the “notebook personal computer P1” in the period Tn, the number of users having the combination of genes “G1a-G2a” is set as a variable Y. In such a state, as shown in FIG. 7C, the analysis unit 132 counts the variable X and the variable Y every period Tn corresponding to the time series. For example, the analysis unit 132 determines the number of users who purchased the “notebook computer P1” in “January 1 to 20 January 31, 2017” (period T1), and a combination of genes among the number of users. Count the number of users having “G1a-G2a”. Similarly, the analysis unit 132 counts for each period Tn. Here, it is assumed that the analysis unit 132 has obtained the count result as shown in FIG. 7 (c).

  The analysis unit 132 uses this count result to determine whether a user who performs purchasing behavior such as "buy notebook PC P1" tends to have a combination of genes "G1a-G2a", that is, purchasing behavior "laptop computer P1. It is analyzed whether a correlation is established between the “buy” and the gene combination “G1a-G2a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. Then, if the calculated correlation coefficient is, for example, a predetermined value or more, the analysis unit 132 establishes a correlation between the purchase behavior “buy notebook PC P1” and the combination of genes “G1a-G2a”. , Get correlation analysis results. On the other hand, if the calculated correlation coefficient is equal to or less than a predetermined value, the analysis unit 132 indicates that the purchase behavior “buy notebook PC P1” is not correlated with the combination of genes “G1a-G2a”. Get

  In FIG. 7, the purchasing behavior “buy notebook PC P1” and the combination of genes “G1a-G2a” have been described as an example, but the analysis unit 132 is not limited to each product (for example, suit P2, sake P3 etc.) The correlation between the purchase information corresponding to and the gene information (for example, “G1a-G2b”, “G1b-G2a”, etc.) corresponding to the combination of each gene is analyzed, and the correlation coefficient is calculated.

(Pattern 3)
Next, pattern 3 will be described with reference to FIG. FIG. 8 is a diagram schematically showing an example of an analysis method for analyzing the relationship between behavior information and gene information. In pattern 3, the analysis unit 132 performs correlation analysis between a combination of a plurality of pieces of action information among the acquired pieces of action information and each piece of gene information to thereby obtain a combination of a plurality of pieces of action information and each piece of gene information. Analyze whether correlation is established. In pattern 3, a combination of a plurality of pieces of action information is a product group belonging to each of the product categories. However, the present invention is not limited to this example, and the combination of the plurality of behavior information may be, for example, all combinations assumed by combining the products.

  First, the analysis unit 132 refers to the gene information storage unit 121 and lists up users having the gene for each gene. Specifically, as shown in FIG. 8A, the analysis unit 132 gives “1” to the user who has the gene for each gene contained in the gene information, and has the gene for each gene. “0” is given to users who do not. For example, in the example of the gene information storage unit 121 shown in FIG. 4, it is understood from the gene information rd11 that the user U1 has the gene “G1a”. Therefore, as shown in FIG. 8A, the analysis unit 132 assigns “1” to the input field corresponding to the gene “G1a” and the user ID “U1”. Then, the analysis unit 132 generates a gene-user list as shown in FIG. 8 (a).

  Further, the analysis unit 132 refers to the purchase history storage unit 122, and lists up the users who have purchased the product in each category during the period Tn (period according to the time series). Here, the period T1 is set to "one month", and this one month is further set as "January 1 2017-January 31 17". In such a state, as shown in FIG. 8B, the analysis unit 132 may include a product included in purchase information regarding purchases performed between “January 1, 2017 to January 31, 2017”. Among the items, “1” is given to the user who has purchased the item for each item belonging to each category, and “0” is given to the user who has not purchased the item for each item. For example, as shown in FIG. 8B, the analysis unit 132 assigns “1” to the input field corresponding to the category “PC body” and the user ID “U1”. Then, the analysis unit 132 generates a product category-user list as shown in FIG. 8 (b).

  Also, similarly, the analysis unit 132 belongs to each category among the products included in the purchase information related to the purchase performed during “February 1, 2017 to February 29, 2017” (period T2). A product category-user list is generated by assigning “1” to a user who purchases the product for each product and assigning “0” to a user who has not purchased the product for each product. Do. That is, the analysis unit 132 generates a merchandise category-user list for each period Tn. Also, although the category "PC body" has been described as an example, as shown in FIG. 8 (b), the analysis unit 132 is such as category "male suit" and category "alcohol" for each period Tn for each category. The product category-user list is generated.

  Hereinafter, an example of a correlation analysis between the purchase behavior “buy a product belonging to the category“ personal computer ”” and the gene information “G1a” will be described. First, let the variable X be the number of users who have purchased a product belonging to the category “PC body” in the period Tn. Further, among the number of users who purchased products belonging to the category “PC body” during the period Tn, the number of users having the gene “G1a” is set as a variable Y. In such a state, as illustrated in FIG. 8C, the analysis unit 132 counts the variable X and the variable Y for each period Tn corresponding to the time series. For example, the analysis unit 132 determines the number of users who have purchased a product belonging to the category "PC body" in "January 1 to 20 January 31, 2017" (period T1), and the number of users among these users. The number of users having the gene “G1a” is counted. Similarly, the analysis unit 132 counts for each period Tn. Here, it is assumed that the analysis unit 132 has obtained the count result as shown in FIG.

  Then, using the count result, the analysis unit 132 determines whether a user who performs purchasing behavior such as "Buy a product belonging to the category" PC body "" tends to have the gene "G1a", that is, purchasing behavior "category" An analysis is made as to whether a correlation is established between the purchase of a product belonging to the “PC body” and the gene information “G1a”. Specifically, the analysis unit 132 calculates a correlation coefficient using the count result. Then, if the calculated correlation coefficient is, for example, a predetermined value or more, the analysis unit 132 has a correlation between the purchasing behavior “buy a product belonging to the category“ PC body ”” and the gene information “G1a”. Correlation analysis result is obtained. On the other hand, if the calculated correlation coefficient is equal to or less than a predetermined value, the analysis unit 132 indicates that the purchase behavior “buy a product belonging to the category“ PC body ”” is not correlated with the gene information “G1a”. Obtain analysis results.

  In FIG. 8, the purchasing behavior “buy a product belonging to the category“ PC body ”” and the gene information “G1a” have been described as an example, but the analysis unit 132 is not limited to each category (for example, a male suit, liquor, etc.) The correlation between the purchase information corresponding to) and gene information (for example, G1 b, G2 a, etc.) corresponding to each gene is analyzed to calculate a correlation coefficient.

(About the specific part 133)
Referring back to FIG. 3, the identifying unit 133 determines a predetermined relationship between the user's behavior information and the user's gene information acquired by the acquiring unit 131 based on the analysis result obtained from the correlation analysis by the analysis unit 132. Identify genetic information having a sex (eg, correlation). In other words, the specifying unit 133 specifies a combination of correlated genetic information and behavior information among the user's genetic information and behavior information. For example, the specifying unit 133 specifies that there is a correlation with the behavior information and the gene information for which the analysis unit 132 has obtained a correlation result with a correlation coefficient equal to or greater than a predetermined value.

(About the providing unit 134)
The providing unit 134 provides information based on the user's genetic information to a target person having behavior information related to the user's behavior information. For example, the providing unit 134 uses the user purchase information as the user behavior information by the acquisition unit 131 and uses the analysis unit 132 when the relationship between the behavior information and the gene information is analyzed by the analysis unit 132 as described above. Information based on gene information having a predetermined relationship with the action information of the user among the gene information of the person is provided to a target person having action information related to the action information of the user.

  Here, it is assumed that the purchasing unit “buy sake P3” and the gene “G2b” are specified to be correlated by the identifying unit 133. In other words, the identifying unit 133 identifies a tendency indicating a correlation that the user “buy sake P3” tends to have the gene “G2b”.

  In this example, the providing unit 134 predicts that the target person who performs the purchasing action of “buy sake P3” has the gene “G2b”. For example, the following can be considered as the ground that can be predicted in this way. Specifically, "buy sake P3" is "drinker", and such a person is "stronger against liquor", so the gene resulting from the production of alcohol metabolizing enzyme with stronger enzyme activity There is a high possibility of having "G2b".

  Therefore, providing unit 134 predicts that the target person who carries out a purchasing action such as "buy sake P3" as having the gene "G2b", and actually the gene "G2b" has alcohol metabolism with stronger enzyme activity. If it is determined that the gene is attributable to producing an enzyme, information may be provided.

  That is, the providing unit 134 is a gene whose gene information having a predetermined relationship (for example, correlation) with the user's action information is a gene caused by prediction information (for example, constitution or disease) predicted from the action information. Determine if there is. Then, when it is determined that the gene is the cause, the providing unit 134 may provide information based on the gene information to the subject having the action information related to the action information. Note that such a determination process may be performed by a processing unit (for example, a determination unit) other than the providing unit 134. Now, an example of information provision by the provision unit 134 will be described below.

  For example, since the information providing apparatus 100 is registered as a member at the management company T, among users who have an account with the management company T, the information provision apparatus 100 has performed purchasing behavior such as "buy sake P3". The user is extracted from the purchase history storage unit 122. Next, the information providing apparatus 100 extracts, from among the extracted users, a user having no gene information, that is, a user who does not know what gene it has as a target person. Here, it is assumed that the information providing apparatus 100 has extracted the user Ux.

  In such a case, the providing unit 134 predicts that the user Ux extracted as the target person also has the gene “G2b”. Then, the providing unit 134 provides the user Ux with information based on the gene information “G2b”. For example, the providing unit 134 provides information based on related information related to the gene information “G2b”. The related information related to the genetic information “G2b” is, for example, information on the constitution or disease having the genetic information “G2b” as a factor. Therefore, the providing unit 134, for example, performs recommendation and alert on constitution and disease as information provision based on gene information.

  The providing unit 134 may perform such information provision at any timing and in any display mode. For example, when the providing unit 134 receives a delivery request for a predetermined web page from the user terminal 10 of the user Ux, the providing unit 134 delivers a web page on which information based on genetic information is displayed to the user terminal 10. Good.

[4. Processing procedure)
Next, the procedure of the providing process performed by the information providing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 9 is a flowchart showing the overall flow of the providing process by the information providing apparatus 100 according to the embodiment.

  First, the information providing apparatus 100 acquires behavior information indicating a user's behavior on the network and the user's genetic information (step S101). For example, the information providing apparatus 100 acquires gene information from the inspection agency server 30, which is a server device of a predetermined inspection agency. Further, the information providing device 100 acquires behavior information from the external server 60 that accumulates various behavior information.

  Next, the information providing apparatus 100 analyzes the relationship between the behavior information and the gene information (step S102). Specifically, the information providing apparatus 100 analyzes whether a predetermined relationship is established between the behavior information and the gene information. For example, the information providing apparatus 100 analyzes whether the relationship based on the tendency between the behavior information and the gene information, that is, the correlation is established as the predetermined relationship.

  Next, the information providing apparatus 100 identifies gene information having a correlation (correlation) with the behavior information of the user among the genetic information of the user from the analysis result in step S102 (step S103). .

  Then, the information providing apparatus 100 provides information based on the gene information to the subject having the action information related to the action information found to be correlated with the gene information specified in step S103 ( Step S104).

[5. (Modification)
The information providing apparatus 100 according to the embodiment may be implemented in various different forms other than the above example. Therefore, another embodiment will be described below.

[5-1. Search behavior)
In the above embodiment, the information providing apparatus 100 acquires purchase information as action information, and among gene information, information based on gene information having a predetermined relationship with the purchase information is associated with the action information of the user. The example provided with respect to the subject who has action information was shown. However, the information providing apparatus 100 may acquire information related to search as behavior information and provide information to a target person who has behavior information related to information related to the search.

  Specifically, the acquisition unit 131 acquires search behavior information that is information related to a search performed by a user using a search keyword as user behavior information. The analysis unit 132 also analyzes the relationship between the search behavior information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the search behavior information and the gene information.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the user's search behavior information from the user's genetic information based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of gene information and search behavior information in correlation among the user's gene information and search behavior information. Then, the providing unit 134 performs the search behavior related to the search behavior indicated by the search behavior information on the information based on the genetic information having a predetermined relationship with the search behavior information among the genetic information of the user. To provide Hereinafter, an example of the providing process will be described. In addition, although the example which uses purchase information as action information was shown in the said embodiment, this modified example uses search action information instead of purchase information. Therefore, description of the common processing will be simplified as appropriate.

  For example, the acquisition unit 131 acquires search behavior information that is information related to a search performed by a user using a search keyword by accessing the external server 60 (for example, a search server). The search behavior information is information indicating a search behavior, such as which user has performed information search using what kind of search keyword. Therefore, the search behavior information can be said to be a search history. The acquisition unit 131 stores the acquired search behavior information in the search history storage unit 123 as illustrated in FIG. The search history storage unit 123 is a storage unit included in the storage unit 120.

  FIG. 10 is a diagram illustrating an example of the search history storage unit 123 according to the embodiment. In the example of FIG. 10, the search history storage unit 123 includes items such as “user ID”, “search keyword”, and “search date / time”. “User ID” indicates identification information for identifying the user who performed the search. The gene information stored in the gene information storage unit 121 and the search behavior information stored in the search history storage unit 123 are associated with the same user ID. “Search keyword” indicates a search keyword used (input) by a corresponding user. “Search date and time” indicates the date and time when the search was performed by the corresponding user. That is, the example of FIG. 10 shows an example in which the user U1 performs a search action using the search keyword “travel” on “January 10, 2017”.

  Further, as described in the above embodiment, the analysis unit 132 can analyze whether or not a correlation is established between the search behavior information and the gene information by using three patterns of analysis methods.

  In Pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each behavior information and each gene information by performing a correlation analysis between each search behavior information and each gene information. For example, the analysis unit 132 generates a gene-user list as described in FIG. 6 (a). Moreover, the analysis part 132 produces | generates the goods-user list for every period Tn for every search action (each search keyword). Such a list corresponds to a product replaced with each search keyword (for example, travel, job change, etc.) in the product-user list for each period Tn shown in FIG.

  Then, the analysis unit 132 analyzes the correlation between search action information information corresponding to each search keyword and gene information corresponding to each gene, and calculates a correlation coefficient. For example, the analysis unit 132 uses the search keyword “travel” during the period T1 as a variable X, and searches using the search keyword “travel” during the period T1. Among the number of users, the number of users having the gene "G1a" is counted as a variable Y, and these variables are counted. Then, the analysis unit 132 determines that the user who searches using the search keyword “travel” has the gene “G1a”, that is, the search action “searches using the search keyword“ travel ”” and the gene information “ The correlation coefficient is calculated by performing correlation analysis on whether the correlation with the G1a "is established. Similarly, the analysis unit 132 performs counting for each period Tn.

  In Pattern 2, the analysis unit 132 performs correlation analysis between each search behavior information and a combination of a plurality of pieces of gene information among the acquired gene information, so that each search behavior information and a combination of a plurality of gene information are Analyzes whether a correlation is established between them. For example, the analysis unit 132 generates a gene combination-user list as described in FIG. 7A. Moreover, the analysis part 132 produces | generates the goods-user list for every period Tn for every search action (each search keyword). Such a list corresponds to a product replaced with each search keyword (for example, travel, job change, etc.) in the product-user list for each period Tn shown in FIG.

  Then, the analysis unit 132 analyzes the correlation between the search behavior information information corresponding to each search keyword and the gene information corresponding to each combination of genes, and calculates a correlation coefficient. For example, the analysis unit 132 uses the search keyword “travel” during the period T1 as a variable X, and searches using the search keyword “travel” during the period T1. Among the number of users, the number of users having the gene combination “G1a-G2a” is defined as a variable Y, and these variables are counted. Then, the analysis unit 132 has a tendency that the user who searches using the search keyword “travel” has the gene combination “G1a-G2a”, that is, the search action “searches using the search keyword“ travel ””. A correlation coefficient is calculated by performing correlation analysis whether there is a correlation between the gene and the combination of genes "G1a-G2a". Similarly, the analysis unit 132 performs counting for each period Tn.

  In the pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of search behavior information in the acquired search behavior information and each gene information, so that the combination of the plurality of search behavior information and each gene information Whether or not a correlation is established. In the pattern 3, it is assumed that a combination of a plurality of search behavior information is a search keyword group belonging to each category of search keywords. An example is a search keyword belonging to the search category “alcohol”. However, the present invention is not limited to this example, and the combination of the plurality of search behavior information may be, for example, all combinations assumed by combining the search keywords.

  For example, as described in FIG. 8A, the analysis unit 132 generates a gene-user list. Further, the analysis unit 132 generates a search category-user list for each period Tn for each search category. This list corresponds to the product category-user list in each of the periods Tn shown in FIG. 8B, in which the product is replaced with each search category.

  And the analysis part 132 calculates a correlation coefficient by analyzing the correlation of the search action information corresponding to each search category, and the gene information corresponding to each gene. For example, the analysis unit 132 sets the number of users who have searched for a search keyword belonging to the search category “PC” in the period T1 as a variable X, and uses the search keyword belonging to the search category “PC” in the period T1. Among the number of users who have searched, the number of users having the gene “G1a” is taken as a variable Y, and these variables are counted. Then, the analysis unit 132 determines whether a user who performs a search with a search keyword belonging to the search category “computer” has a gene “G1a”, that is, performs a search with a search keyword belonging to the search action “search category“ computer ””. A correlation coefficient is calculated by performing a correlation analysis to determine whether a correlation is established between “perform” and the gene “G1a”.

  Here, it is assumed that the specifying unit 133 specifies that the search behavior “search using the search keyword“ beer ”” and the gene “G2b” are correlated from the correlation analysis result. In other words, the specifying unit 133 specifies a tendency indicating a correlation such that a user who “searches with the search keyword“ beer ”tends to have the gene“ G2b ”. In such an example, the providing unit 134 determines the gene “G2b” for the user Ux who is a target person who has performed a search action such as “search with the search keyword“ beer ”” although the genetic information is undecided. Provide information based on

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific search action from the target persons whose unknown gene information is unknown, More suitable information can be provided to the subject who predicted the information.

[5-2. (Advertising browsing behavior)
In addition, the information providing apparatus 100 may obtain, as the action information, information on browsing of the advertisement content, and may provide information to the target person having the action information related to the information on the advertisement browsing.

  Specifically, the acquisition unit 131 acquires, as the action information of the user, advertisement browsing information which is information related to a browsing action in which the user browses the advertisement content. The analysis unit 132 also analyzes the relationship between the advertisement browsing information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the advertisement browsing information and the gene information.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the advertisement browsing information of the user among the gene information of the user based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of gene information and search behavior information that are correlated among the user's gene information and the advertisement browsing information. And the provision part 134 performed the browsing action relevant to the browsing action shown by the said advertisement browsing information about the information based on the genetic information which has a predetermined relationship with advertisement browsing information among a user's genetic information. To provide

  For example, the acquisition unit 131 accesses the external server 60 (for example, a content server) to acquire advertisement browsing information, which is information related to browsing behavior in which the user browses the advertisement content. The advertisement browsing information is information indicating a search action, such as which user browsed which advertisement content. Therefore, it can be said that the advertisement browsing information is an advertisement browsing history. Note that any case may be defined as a user viewing an advertisement. For example, when the user selects advertising content, the selected advertising content may be defined as viewed. Also, the advertisement content delivered to the user may be defined as browsed. In this modification, it is determined that the advertisement content selected by the user is viewed by the user.

  The acquisition unit 131 stores the acquired advertisement browsing information in the browsing history storage unit 124 as illustrated in FIG. The browsing history storage unit 124 is a storage unit included in the storage unit 120. FIG. 11 is a diagram illustrating an example of the browsing history storage unit 124 according to the embodiment. In the example of FIG. 11, the browsing history storage unit 124 has items such as “user ID”, “advertising content”, and “browsing date”.

  The “user ID” indicates identification information for identifying a user who browsed the advertisement content. The gene information stored in the gene information storage unit 121 and the advertisement browsing information stored in the browsing history storage unit 124 are associated with the same user ID. “Advertising content” indicates the advertising content browsed by the corresponding user. "Reading date" indicates the date when the advertisement content was read by the corresponding user.

  Moreover, the analysis part 132 can analyze whether correlation is established between advertisement browsing information and gene information using the analysis method of 3 patterns, as demonstrated in the said embodiment. In Pattern 1, the analysis unit 132 analyzes whether or not a correlation is established between each advertisement browsing information and each gene information by performing a correlation analysis between each advertisement browsing information and each gene information. In Pattern 2, the analysis unit 132 performs correlation analysis between each advertisement browsing information and a combination of a plurality of pieces of gene information among the acquired gene information, so that each advertisement reading information and a combination of a plurality of gene information are Analyzes whether a correlation is established between them. In Pattern 3, the analysis unit 132 performs a correlation analysis between a combination of a plurality of advertisement browsing information among the acquired advertisement browsing information and each gene information, so that the combination of the plurality of advertisement browsing information and each gene information Whether or not a correlation is established.

  Here, for example, it is assumed that the specifying unit 133 specifies from the correlation analysis result that the browsing action “view advertising content related to beer” and the gene “G2b” are correlated. In other words, the specifying unit 133 specifies a tendency indicating a correlation such that a user “browsing advertising content related to beer” tends to have the gene “G2b”. In this example, for example, the providing unit 134 determines the gene “G2b” for the user Ux who is a target person who has performed browsing behavior such as “browsing advertising content related to beer” although genetic information is not yet determined. Provide information based on

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific advertisement browsing behavior, from among the target persons whose genetic information is unknown, More suitable information can be provided to the subject who predicted the genetic information.

[5-3. Article reading behavior]
Also, the advertisement content may be article content. That is, the information providing apparatus 100 may acquire information regarding browsing of article content as the behavior information, and may provide information to a target person having the behavior information related to the information regarding article browsing.

  Specifically, the acquisition unit 131 acquires, as the action information of the user, article browsing information which is information on a browsing action in which the user browses the article content. The article content is, for example, a news article, an economic article, an entertainment-related article, a sports article, a blog, or the like. The analysis unit 132 also analyzes the relationship between the article browsing information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether or not a correlation is established between the article browsing information and the gene information. Although a detailed description of the analysis technique is omitted, patterns 1 to 3 can be used as described above.

  The specifying unit 133 also obtains gene information having a predetermined relationship (for example, correlation) with the user's article browsing information among the user's genetic information based on the analysis result obtained by the analysis unit 131. Identify. That is, the specifying unit 133 specifies a combination of gene information and article browsing information in correlation among the user's gene information and article browsing information. And the provision part 134 performed the browsing action relevant to the browsing action shown by the said article browsing information about the information based on the genetic information which has a predetermined relationship with the article browsing information among the genetic information of the user To provide

  Here, for example, it is assumed that the browsing action “browsing article content related to beer” and the gene “G2b” are specified to be correlated from the correlation analysis result by the specifying unit 133. In such an example, for example, the providing unit 134 determines the gene “G2b” for the user Ux who is a target person who has performed browsing behavior such as “browsing article content related to beer” although genetic information is not yet determined. Provide information based on

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific article browsing behavior from the unknown target person who has what kind of genetic information, More suitable information can be provided to the subject who predicted the genetic information.

[5-4. Stock trading information)
Moreover, the acquisition part 131 may acquire the stock transaction information which is the information regarding the stock transaction which the user performed as a user's action information. Then, the analysis unit 132 analyzes the relationship between the stock transaction information acquired by the acquisition unit 131 and the gene information. For example, the analysis unit 132 analyzes whether a correlation is established between stock trade information and gene information.

  In addition, the identification unit 133 determines, based on the analysis result obtained by the analysis unit 131, gene information having a predetermined relationship (for example, correlation) with the stock transaction information of the user among the user's gene information. Identify. That is, the specifying unit 133 specifies a combination of correlated gene information and stock transaction information among the user's gene information and stock transaction information. Then, the providing unit 134 is a target for which stock trading related to stock trading indicated by the stock trading information is performed on information based on gene information having a predetermined relationship with stock trading information among the user's genetic information. To provide

  For example, the acquisition unit 131 acquires stock transaction information that is information related to stock transactions performed by the user by accessing the external server 60 (for example, a stock transaction management server). The stock exchange information is information indicating stock exchange behavior, such as which user purchased which number of shares of which stock (stock) and when. Further, the acquisition unit 131 stores the acquired stock transaction information as a stock transaction history in a predetermined storage unit (not shown).

  Further, as described in the above embodiment, the analysis unit 132 can analyze whether or not a correlation is established between the stock transaction information and the gene information by using the three patterns of analysis methods. In pattern 1, the analysis 132 analyzes whether or not a correlation is established between each advertisement browsing information and each gene information by performing a correlation analysis between each stock transaction information and each gene information. In pattern 2, the analysis unit 132 performs correlation analysis between each stock transaction information and a combination of a plurality of genetic information among the acquired genetic information to obtain a combination of each stock transaction information and a plurality of genetic information. Analyzes whether a correlation is established between them. In pattern 3, the analysis unit 132 performs correlation analysis between a combination of a plurality of stock transaction information among the acquired stock transaction information and each gene information to obtain a combination of the plurality of stock transaction information and each gene information. Whether or not a correlation is established.

  Here, for example, it is assumed that, from the correlation analysis result, it is specified by the specifying unit 133 that the stock transaction “buy a predetermined number of stocks of a predetermined amount or more per stock” is correlated with the gene “G4a”. . In other words, it is assumed that the specifying unit 133 specifies a tendency indicating a correlation such that a user who “buys a predetermined number of stocks of a predetermined amount or more per share” tends to have the gene “G4a”. For example, if the above-mentioned stock trade that has been associated with the gene “G4a” is, for example, a risky stock trade, the providing unit 134 has a user (referred to as user Ux) having the gene “G4a”. Judges as "rough character" or "tempered character", and proposes to make a cautious stock transaction for the user Ux.

  As a result, the information providing apparatus 100 according to the embodiment can predict the gene information possessed by a target person who carries out a specific stock transaction from among the unknown person who has any gene information. More suitable information can be provided to the subject who predicted the information.

[5-5. About information based on genetic information]
Up to now, examples have been shown in which the presentation unit 134 makes recommendations and alerts based on genetic information as information provision based on the user's genetic information. However, the presentation unit 134 may provide advertising content based on the user's genetic information to a target person having behavior information related to the user's behavior information. For example, as in the above example, the specifying unit 133 specifies that the purchase action “buy sake P3” is correlated with the gene “G2b”, and the gene “G2b” has a stronger enzyme activity. In the case of a gene resulting from the production of an alcohol metabolizing enzyme, the providing unit 134 distributes advertising content related to an over-the-counter drug that is effective for excessive drinking.

  Thereby, since the information providing apparatus 100 according to the embodiment can distribute advertising content more suitable for the target person, the advertising effect can be enhanced.

[5-6. Use prediction information from behavior information]
In the above-described embodiment, an example in which the analysis unit 132 analyzes the relationship between user behavior information and gene information has been described. However, the analysis unit 132 may analyze the relationship between the prediction information predicted from the user behavior information and the gene information. For example, the analysis unit 132 predicts the user's disease (an example of prediction information) from the user's behavior information, and analyzes the relationship between the predicted disease and the gene information. Also, the analysis unit 132 specifies the cause factor of the prediction information based on the analysis result. This point will be described using an example.

  For example, it is assumed that purchasing information including purchasing behavior such as “purchasing over-the-counter medication MD related to diabetes” is acquired by the acquiring unit 131. In such a case, the analysis unit 132 predicts from the purchase information that the user who performs the purchase behavior such as “purchase the over-the-counter drug MD related to diabetes” is “diabetes”. Then, the analysis unit 131 analyzes whether or not a correlation is established between the purchase information “Purchase the over-the-counter medicine MD for diabetes” and the genetic information.

  For example, it is assumed that the analysis unit 132 obtains an analysis result that the purchase information “purchase the over-the-counter drug MD related to diabetes” and the gene information “G3b” are correlated. In such a case, the analysis unit 132 specifies the gene “G3b” as a causative factor for the onset of diabetes.

  Thereby, the information providing apparatus 100 according to the embodiment can newly discover a gene that causes a disease. Further, the information providing apparatus 100 reinforces the existing report contents by comparing the existing report contents (for example, test results by clinical examination, scientific report contents, etc.) with the analysis results by the analysis unit 132. Can.

  The analysis unit 132 may predict the constitution (an example of prediction information) of the user from the user's action information, and analyze the relationship between the predicted constitution and the gene information. Further, the analysis unit 132 may use search behavior information, advertisement browsing information, article browsing information, and the like as the user's behavior information.

[6. Hardware configuration)
Further, the information providing apparatus 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 12, for example. FIG. 12 is a hardware configuration diagram showing an example of a computer 1000 for realizing the functions of the information providing device 100. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program depending on the hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from another device via the communication network 50, sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to the other device via the communication network 50.

  The CPU 1100 controls an output device such as a display and a printer and an input device such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. In addition, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the CPU 1100 with the program via the RAM 1200. The CPU 1100 loads such a program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase change rewritable disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. Etc.

  For example, when the computer 1000 functions as the information providing apparatus 100, the CPU 1100 of the computer 1000 realizes the function of the control unit 130 by executing a program loaded on the RAM 1200. The HDD 1400 stores data in the storage unit 120. The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them. However, as another example, these programs may be acquired from other devices via the communication network 50.

[7. Others]
Further, among the processes described in the above embodiment, all or part of the process described as being automatically performed may be manually performed, or the process described as being manually performed. All or part of them can be performed automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above-mentioned documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. It can be integrated and configured.

  Moreover, it is possible to combine suitably each embodiment mentioned above in the range which does not contradict process content.

[8. effect〕
The information providing apparatus 100 according to the embodiment includes an acquiring unit 131 and a providing unit 134. The acquisition unit 131 acquires behavior information indicating behavior of the user on the network and gene information of the user. The providing unit 134 provides information based on the user's genetic information to a target person having behavior information related to the user's behavior information.

  As described above, the information processing apparatus 100 can provide more appropriate information to the target person by using the behavior information and gene information of the user. For example, the information processing apparatus 100 can predict what kind of gene a target person who can not obtain gene information has, by using the behavior information of the user and the gene information. For this reason, since the information processing apparatus 100 can provide information on a constitution or a disease caused by the gene as a causal factor as information based on the predicted gene to the target person, for example, constitution improvement or disease prevention Can contribute.

  In addition, the providing unit 134 includes, based on the user's genetic information, information based on genetic information having a predetermined relationship with the user's behavior information, and a target person having behavior information related to the user's behavior information. Provide against.

  Thereby, since the information processing apparatus 100 according to the embodiment can predict with high accuracy what kind of gene the target person whose genetic information is unknown, for example, information more suitable for the target person can be obtained. Can be provided.

  Moreover, the acquisition part 131 acquires the search action information which is the information regarding the search which the user performed using the search keyword as a user's action information. Then, the providing unit 134 performs the search behavior related to the search behavior indicated by the search behavior information on the information based on the genetic information having a predetermined relationship with the search behavior information among the genetic information of the user. To provide

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific search action from the target persons whose unknown gene information is unknown, More suitable information can be provided to the subject who predicted the information.

  In addition, the acquisition unit 131 acquires, as the action information of the user, purchase information which is information related to the purchase made by the user. Then, the providing unit 134 sends information based on the genetic information having a predetermined relationship with the purchase information among the genetic information of the user to the target person who has performed the purchase behavior related to the purchase behavior indicated by the purchase information. Provide for.

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific purchase behavior from the target persons whose unknown gene information is unknown, More suitable information can be provided to the subject who predicted the information.

  Moreover, the acquisition part 131 acquires the advertisement browsing information which is the information regarding the browsing action which the user browsed advertisement content as a user's action information. And the provision part 134 performed the browsing action relevant to the browsing action shown by the said advertisement browsing information about the information based on the genetic information which has a predetermined relationship with advertisement browsing information among a user's genetic information. To provide

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific advertisement browsing behavior, from among the target persons whose genetic information is unknown, More suitable information can be provided to the subject who predicted the genetic information.

  Moreover, the acquisition part 131 acquires the article browsing information which is the information regarding the browsing action which the user browsed the article content as a user's action information. And the provision part 134 performed the browsing action relevant to the browsing action shown by the said article browsing information about the information based on the genetic information which has a predetermined relationship with the article browsing information among the genetic information of the user To provide

  Thereby, since the information providing apparatus 100 according to the embodiment can predict the genetic information of the target person who performs the specific article browsing behavior from the unknown target person who has what kind of genetic information, More suitable information can be provided to the subject who predicted the genetic information.

  In addition, the acquisition unit acquires stock transaction information, which is information on stock transactions made by the user, as user behavior information. Then, the providing unit 134 is a target for which stock trading related to stock trading indicated by the stock trading information is performed on information based on gene information having a predetermined relationship with stock trading information among the user's genetic information. To provide

  As a result, the information providing apparatus 100 according to the embodiment can predict the gene information possessed by a target person who carries out a specific stock transaction from among the unknown person who has any gene information. More suitable information can be provided to the subject who predicted the information.

  In addition, the providing unit 134 obtains, as the predetermined relationship, information on gene information having a relationship based on a tendency between the gene information and the user's behavior information among the gene information of the user. Provided to a subject who has behavior information related to the behavior information.

  Thereby, the information processing apparatus 100 according to the embodiment can provide more appropriate information to the target person.

  As described above, some of the embodiments of the present application have been described in detail with reference to the drawings. However, these are merely examples, and various modifications, including the aspects described in the disclosure section of the invention, based on the knowledge of those skilled in the art, It is possible to implement the present invention in other forms with improvements.

  In addition, the "section (module, unit)" described above can be read as "means" or "circuit". For example, the acquisition unit can be read as acquisition means or an acquisition circuit.

DESCRIPTION OF SYMBOLS 1 Information provision system 10 User terminal 30 Inspection organization server 60 External server 100 Information provision apparatus 121 Gene information storage part 131 Acquisition part 132 Analysis part 133 Identification part 134 Provision part

Claims (10)

A storage unit that stores behavior information indicating behavior on the user's network and genetic information of the user;
An acquisition unit that acquires the behavior information and the gene information from the storage unit ;
It is a target person who has action information related to the action information of the user , and the gene of the user is not for the subject whose gene analysis is not performed and gene information is not performed based on the analysis result of the gene analysis. An information providing apparatus comprising: a providing unit that provides information based on information. The providing unit among the genetic information of the user, the information based on genetic information with action information and the predetermined relationship of the user, the subject having an action information associated with the action information of the user The information providing device according to claim 1, wherein the information providing device is provided to the user. The acquisition unit acquires search behavior information that is information related to a search performed by the user using a search keyword as the user behavior information,
The provider performs the search action associated with the search action indicated by the search action information, the information based on the gene information having a predetermined relationship with the search action information among the gene information of the user. The information providing device according to claim 2, wherein the information providing device is provided to a target person. The acquisition unit acquires purchase information, which is information related to purchase performed by the user, as the user behavior information,
The providing unit is configured of the user of genetic information, information based on genetic information with the purchase information and the predetermined relation, the subject performing the purchasing behavior associated with the purchase action indicated by the purchase information The information providing apparatus according to claim 2 or 3, wherein the information providing apparatus is provided. The acquisition unit acquires, as the action information of the user, advertisement browsing information which is information on a browsing action in which the user browses advertisement content,
The providing unit performs the browsing behavior related to the browsing behavior indicated by the advertisement browsing information, the information based on the genetic information having a predetermined relationship with the advertisement browsing information among the genetic information of the user The information providing apparatus according to any one of claims 2 to 4, which is provided to a target person. The acquisition unit acquires, as the action information of the user, article browsing information which is information regarding a browsing action in which the user browses an article content,
The providing unit performs the browsing behavior related to the browsing behavior indicated by the article browsing information, the information based on the genetic information having a predetermined relationship with the article browsing information among the genetic information of the user The information providing apparatus according to any one of claims 2 to 5, which is provided to a subject. The acquisition unit acquires stock transaction information, which is information related to stock transactions performed by the user, as the user behavior information,
The provider performs the stock transaction related to the stock transaction indicated by the stock transaction information, the information based on the gene information having a predetermined relationship with the stock transaction information among the gene information of the user. The information providing apparatus according to any one of claims 1 to 6, which is provided to a target person. The provider provides, as the predetermined relationship, information on gene information having a relationship based on the tendency of the gene information and the action information of the user among the gene information of the user as the predetermined relation. It provides with respect to the said subject who has action information relevant to action information. The information provision apparatus as described in any one of Claims 2-7 characterized by the above-mentioned. An information providing method performed by an information providing apparatus, comprising:
Storing behavior information indicating behavior of the user on the network and gene information of the user in the storage unit;
An acquisition step of acquiring the behavior information and the gene information from the storage unit ;
It is a target person who has action information related to the action information of the user , and the gene of the user is not for the subject whose gene analysis is not performed and gene information is not performed based on the analysis result of the gene analysis. And a providing step of providing information based on the information. A procedure for storing behavior information indicating behavior of the user on the network and gene information of the user in the storage unit;
An acquisition procedure for acquiring the behavior information and the gene information from the storage unit ;
It is a target person who has action information related to the action information of the user , and the gene of the user is not for the subject whose gene analysis is not performed and gene information is not performed based on the analysis result of the gene analysis. An information providing program comprising: causing a computer to execute a providing procedure for providing information based on information.

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