JP5281486B2 - Information processing apparatus, information processing method, and information processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an information processing apparatus that cross-sectionally utilizes differently formatted data such as survey results such that individual survey results are easily recognized and utilized in various activities. <P>SOLUTION: For displaying tabulated results of data sets DS each containing tag information characterizing survey items and raw data that is survey results, the information processing apparatus includes a matching part 10a for comparing the tag information contained in different data sets DS and standardizing the tag information and corresponding raw data according to the comparison results, a tabulation part 10b for calculating tabulated results of data sets DS with standardized tag information and raw data from the standardized tag information and raw data, and a display 15 for displaying the tabulated results of the data sets DS with standardized tag information and raw data such that the data sets DS can be compared. <P>COPYRIGHT: (C)2011,JPO&amp;INPIT

Description

  The present invention belongs to a technical field of an information processing apparatus, an information processing method, an information processing program, and a data structure. More specifically, it belongs to the technical field of information processing apparatuses and information processing methods for performing information processing related to surveys such as so-called questionnaire surveys, programs for the information processing apparatuses, and data structures.

  In general, many companies, newspaper companies, local governments or ministries conduct statistical surveys such as market surveys and public opinion surveys with the aim of knowing the actual conditions and needs of consumers and consumers. Yes.

  For example, in order for a company to develop marketing activities such as effective advertising and product planning to consumers, the consumer's tastes and hobbies that are the subject of such activities, or products that are the subject of such advertising and product planning, etc. It is effective to understand the way of thinking. For this reason, conventionally, a so-called questionnaire survey is performed on the consumer, and the results are aggregated / analyzed and used for creating an advertisement.

  On the other hand, the questionnaire is generally conducted by a company that manufactures and sells the product or the like, or an advertising agent that represents advertisement of the product or the like. Therefore, if you want to create advertisements for your products after referring to the results of a questionnaire survey on similar products (for example, similar products of other companies), the survey results from the supplier who conducted the questionnaire survey. Need to get the data.

  However, in this case, it is rare that the format (form) of the data is the same as the format used by the company, and therefore, in order to utilize the data of the obtained survey results, for example, it can be widely browsed in the company. In this way, processing such as correcting the format according to the company's own is required.

  Here, as a conventional technique used when handling data of different data formats as described above, there is one disclosed in Patent Document 1, for example. In the technique described in Patent Document 1, data for normalization that covers all items constituting data such as the above-described survey results described in different data formats is temporarily generated, and the data for normalization is generated. Each data format is shared by using data.

Japanese Laid-Open Patent Publication No. 9-305452 (FIGS. 1, 4, 5, etc.)

  However, when the technique described in Patent Document 1 described above is simply applied to a questionnaire survey, the normalization data is generated not based on the questionnaire itself but based on the data obtained as a result of the survey. (For example, depending on the year) or for the convenience of the practitioner (for example, changes in the specifications of advertising objects), the survey results will inevitably differ, so it is necessary to regenerate normalization data for each change. There is a problem that there is.

  In addition, even for questionnaire surveys of different questions, it may be considered that they are based on the same question due to the aggregation of the survey results. There is also a problem in that it is necessary to create a double storage resource, which leads to wasteful use of hardware storage resources.

  Therefore, the present invention has been made in view of the above-mentioned problems, and the problem is that even if the data is a survey result or the like having a different format, each survey result can be obtained by utilizing these data in a cross-sectional manner. To provide an information processing apparatus and information processing method that can be easily recognized and used for various activities, a program for the information processing apparatus, and a data structure.

In order to solve the above-mentioned problem, the invention according to claim 1 is an aggregation related to a plurality of data sets each including tag information characterizing a survey item and result information indicating a survey result for the survey item. An information processing apparatus for notifying a result, wherein the tag information included in each data set is compared between a data set storage means such as a storage device for storing each data set and the different data sets. Based on the comparison means such as a matching processing unit and the comparison result by the comparison means, the tag information and the result information corresponding to the investigation item characterized by the tag information are shared between the different data sets. Using the common means such as the matching processing unit to be used, the common tag information and the result information, and Totaling means such as a totaling unit that calculates a totaling result for each data set for which information is shared for each data set, and each data set for which the tag information and the result information are standardized Notification means such as a display for notifying the calculated total result so that the data sets can be compared with each other, and the commoning means includes candidate tag information that is a candidate for the tag information after commonization. When the candidate storage means such as a matching processing unit to be stored and the tag information to be shared are not the same, the candidate tag information related to the sharing is extracted from the stored candidate tag information Extraction means such as a matching processing unit, candidate notification means for notifying the extracted candidate tag information, and the tag information after sharing from the extracted candidate tag information Selection means of the operating unit or the like used for selecting the candidate tag information, Ru comprising a.

Therefore, based on the result of comparing each tag information between different data sets, the tag information and the corresponding result information are made common between the different data sets, and the tag information and the result information are made common. Aggregate results related to the set are calculated for each data set, and the aggregated results are announced so that they can be compared between the data sets that are subject to standardization. Survey results can be easily recognized.
In addition, when tag information to be shared is not the same, candidate tag information that becomes tag information after sharing is selected from candidate tag information that is a candidate for tag information after sharing. Even tag information that cannot be shared can be shared.

  In order to solve the above-mentioned problem, the invention according to claim 2 is the information processing apparatus according to claim 1, wherein the common means is the identity or similarity of the tag information to be shared. Including dictionary information storage means such as a dictionary data storage unit that stores preset dictionary information and executes the sharing of the tag information based on the stored dictionary information Configured as follows.

  Therefore, since tag information is shared based on preset dictionary information, more appropriate tag information can be shared based on empirical rules.

In order to solve the above problem, the invention according to claim 3 is the information processing apparatus according to claim 1, wherein the sharing means includes the tag information to be shared, and the tag information to be shared. A designation means such as an operation unit used for designating tag information is provided.

  Therefore, even when automatic sharing is not possible, tag information can be shared manually.

In order to solve the above-mentioned problem, the invention according to claim 4 is an aggregation related to a plurality of data sets each including tag information characterizing a survey item and result information indicating a survey result for the survey item. A computer included in an information processing apparatus for notifying a result and including a selection means includes a data set storage means for storing each of the data sets, and each data set between the different data sets. The tag information and the result information corresponding to the investigation item characterized by the tag information are different from each other based on the comparison means by which the tag information is compared and the comparison result by the computer functioning as the comparison means. Using the common means for sharing the data sets, the common tag information, and the result information Aggregating means for calculating, for each data set, an aggregation result related to each data set in which the tag information and the result information are shared, and each data in which the tag information and the result information are shared An information processing program that functions as a notification control unit that controls the notification unit so as to notify the calculated result of the set so that the respective data sets can be compared with each other, and functions as the common unit The candidate storage means for storing candidate tag information that is a candidate for the tag information after sharing the computer, and when the tag information that is the target of the sharing is not the same, the stored candidate tag information An extraction means for extracting the candidate tag information related to the commonization from the inside, and the extracted candidate tag information is notified to the candidate notification means That candidate notification control means, to function as the selection unit is used to select the candidate tag information serving as the tag information after common from the extracted candidate tag information.

Therefore, by reading and executing the information processing program on the computer, the tag information and the corresponding result information are transferred between the different data sets based on the result of comparing the tag information between the different data sets. Can be calculated for each data set, and the totaled results can be compared between the data sets that have been shared. Since the computer functions in such a way as to notify, it is possible to easily recognize a survey result that crosses these data sets even when the survey items are different.
Further, when the tag information to be shared is not the same, the computer functions to select candidate tag information to be the tag information after sharing from the candidate tag information that is a candidate for the tag information after sharing. Therefore, even tag information that cannot be mechanically identical can be shared.

In order to solve the above-mentioned problem, the invention according to claim 5 is an aggregation related to a plurality of data sets each including tag information characterizing a survey item and result information indicating a survey result for the survey item. An information processing apparatus for notifying a result, comprising: a data set storage unit that stores each of the data sets; a candidate storage unit; and a selection unit. The comparison step for comparing the tag information included in each data set between the different data sets, and the investigation items characterized by the tag information and the tag information based on the comparison result in the comparison step The corresponding result information is made common among the different data sets, and the common tag information and the connection information are shared. Using the information, the tag information and the result information are shared with the tabulation process for calculating the tabulation result of each data set for which the tag information and the result information are shared for each data set. the calculated aggregate result for each said data set, saw including a notification step, the comparing capable notice in the each dataset among said candidate storing means, and the candidate of said tag information after common Candidate tag information is stored, and when the tag information to be shared is not identical, the candidate tag information related to the commonization is stored among the stored candidate tag information. An extraction step of extracting, and a candidate notification step of notifying the extracted candidate tag information, wherein the selecting means becomes the tag information after sharing from the extracted candidate tag information It is used to select the candidate tag information.

Therefore, based on the result of comparing each tag information between different data sets, the tag information and the corresponding result information are made common between the different data sets, and the tag information and the result information are made common. Aggregate results related to the set are calculated for each data set, and the aggregated results are announced so that they can be compared between the data sets that are subject to standardization. Survey results can be easily recognized.
In addition, when tag information to be shared is not the same, candidate tag information that becomes tag information after sharing is selected from candidate tag information that is a candidate for tag information after sharing. Even tag information that cannot be shared can be shared.

According to the present invention, the tag information and the corresponding result information are shared between the different data sets based on the result of comparing the tag information between the different data sets, and the tag information and the result information are shared. Calculation results for each data set, and the results of the calculation are announced so that they can be compared between the data sets that are subject to standardization. Survey results across these can be easily recognized.
In addition, when tag information to be shared is not the same, candidate tag information that becomes tag information after sharing is selected from candidate tag information that is a candidate for tag information after sharing. Even tag information that cannot be shared can be shared.

  Therefore, it is possible to effectively and easily recognize the survey results of different data sets and to make extensive use of them for activities such as advertisement creation.

It is a block diagram which shows the schematic structure of the totalization apparatus which concerns on embodiment. It is a figure which illustrates the data structure in the data set concerning an embodiment. It is a flowchart which shows the total process which concerns on embodiment, (a) is a figure which shows the whole said flowchart, (b) is a figure which shows the detail of the said flowchart. It is a figure which illustrates the matching process between the tag information which concerns on embodiment, (a) is a figure which illustrates the matching process between two question sentences, (b) is the degree of similarity between question sentences, and tag information It is a figure which illustrates the relationship with the state of matching between. It is a figure which shows the example of a display of the total result which concerns on embodiment, (a) is a figure I which illustrates the total result before the analysis of the similarity degree of the question sentence by tag information, (b) is a question sentence by tag information FIG. 2C is a diagram illustrating an example of a totaling result before analysis of the similarity of FIG. 3C, FIG. 3C is a diagram illustrating a totaling result of the similarity of the question sentence based on the tag information before the analysis, and FIG. It is a conceptual diagram which shows the relationship between the question sentence between the data sets after analysis of similarity, and a total result, (e) is a figure which illustrates the total result after analysis of the similarity of the question sentence by tag information. It is a figure which illustrates the data structure etc. in the database which concerns on a 1st modification, (a) is a figure which illustrates the production | generation operation | movement of tag information which concerns on a 1st modification, (b) illustrates the said data structure. FIG.

(I) Embodiment First, an embodiment for carrying out the present invention will be described with reference to FIGS. In addition, the embodiment described below and each modification form a total that presents a total result that can be acquired as a result of a questionnaire survey so that it can be recognized, for example, in chronological order or for each target of the questionnaire. This is an embodiment when the present invention is applied to an apparatus.

  FIG. 1 is a block diagram illustrating a schematic configuration of a counting device according to the embodiment, FIG. 2 is a diagram illustrating a data structure of a data set according to the embodiment, and FIG. 3 illustrates a counting process according to the embodiment. It is a flowchart to show. FIG. 4 is a diagram illustrating a matching process between tag information according to the embodiment, and FIG. 5 is a diagram illustrating a display example of a counting result according to the embodiment.

  As shown in FIG. 1, the aggregation device S according to the embodiment is specifically realized by a server device or a personal computer. Then, the aggregation device S stores in the storage devices M1 to Mn as an example of a data set storage unit such as a hard disk drive that stores the first data set DS1 to the nth data set DSn according to the embodiment separately and in a nonvolatile manner. On the other hand, data can be exchanged between each other.

  Here, the data structures of the first data set DS1 to the n-th data set DSn according to the embodiment will be described with reference to FIG. Note that the first data set DS1 to the nth data set DSn according to the embodiment have the same data structure, and therefore, in the following description, the data structure of the first data set DS1 will be described on behalf of them. .

  As illustrated in FIG. 2, the first data set DS1 according to the embodiment includes label data RB corresponding to a question item (question sentence) in the conducted questionnaire survey, and an answer result itself for each question sentence (that is, , And the raw data RD which is the answer result of each respondent to each question sentence). This raw data RD is data indicating the content itself that each respondent answered to the question sentence before counting up as a questionnaire survey. One data set DS corresponds to a questionnaire survey that should be put together, such as a questionnaire survey conducted at the same time, a questionnaire survey conducted with the same purpose, or a questionnaire survey targeting the same scope of subjects. It consists of label data RB and row data RD.

  Next, in the label data RB, the question sentence identification information IDQ1, the question sentence identification information IDQ2, the question sentence identification information IDQ3,..., The question sentence identification information IDQm for identifying each question sentence, and the respective question sentences are respectively stored. Tag information TG1-1 to be characterized, tag information TG1-2,..., Tag information TGm-n are configured and included so as to be paired for each question sentence.

  At this time, in the case illustrated in FIG. 2, a total of n tag information TG1 characterizing the content of the first question sentence is associated with the question sentence identification information IDQ1 for identifying the first question sentence. It is remembered. Specifically, the tag information TG1-1 to the tag information TG1-n have contents that specifically characterize the contents of the first question sentence (identification sentence identified by the question sentence identification information IDQ1) to which they correspond. For example, tag information TG1-1 indicating that the first question sentence is a gender-related question sentence, and an implementation time of a questionnaire survey including the first question sentence (for example, April 2009) Tag information TG1-2 to be displayed, tag information TG1-3 to indicate that the first question sentence is a question sentence in a form of selecting an answer from a plurality of options, and the first question sentence is intended for an adult The tag information TG1 saying tag information TG1-4,... Similarly, for each of question sentence identification information IDQ2, question sentence identification information IDQ3, question sentence identification information IDQ4,..., Question sentence identification information IDQm for identifying each question sentence from other question sentences. The tag information TG2, the tag information TG3, the tag information TG4,..., And the tag information TGm that characterize each of the question sentences are stored in association with each other in a paired relationship.

  Note that the number of tag information TG that characterizes each question sentence (in the case of FIG. 2, n for all question sentences) is not the same as each other and may be different for each question sentence. Further, the tag information TG that characterizes each question sentence may be arbitrarily given for each question sentence by the administrator of the totaling device S, or may be automatically given as in a first modification described later.

  On the other hand, in the raw data RD that is the answer content itself to the question sentence, the question sentence identification information IDQ1, the question sentence identification information IDQ2, the question sentence identification information IDQ3,. , Question sentence identification information IDQm, answerer identification information IDS1, answerer identification information IDS2, answerer identification information IDS3,..., Answerer identification information IDSx for identifying respondents who answered the respective question sentences , Answer information A1-1, answer information A1-2, answer information A1-3,..., Answer information Ax-, which are the answer contents themselves answered by each respondent to each question sentence. m is included.

  At this time, in the case illustrated in FIG. 2, the content itself answered by the respondent identified by the respondent identification information IDS1 with respect to the first question sentence is the answer information A1-1, and similarly the second question The content itself answered by the respondent to the sentence is the reply information A1-2. In addition, the content itself that the respondent identified by the respondent identification information IDS2 responds to the first question is the response information A2-1. Similarly, the respondent answers the second question. The content itself is the answer information A2-2. Similarly, the content itself answered by the respondent identified by the respondent identification information IDSx with respect to the m-th question sentence is the reply information Ax-m.

  The first data set DS1 to the nth data set DSn each having the above-described data structure and each including the label data RB and the row data RD corresponding to the questionnaire survey to be combined into one are individually independent. The data is stored in the storage devices M1 to Mn so that data can be exchanged with the counting device S.

  Next, a detailed configuration of the totalization device S that can exchange data with each of the storage devices M1 to Mn will be described with reference to FIGS.

  As illustrated in FIG. 1, the aggregation device S according to the embodiment includes an example of a comparison unit, an example of a sharing unit, an example of a candidate storage unit, an example of an extraction unit, and a matching processing unit 10a and an example of an aggregation unit. As an example of a dictionary information storage means including a main control unit 10 functionally including a totaling unit 10b, a volatile RAM (Random Access Memory) 11, a nonvolatile ROM (Read Only Memory) 12, and a hard disk or the like. Dictionary data storage unit 13, an example of a selection unit including an input device such as a keyboard and a mouse, an operation unit 14 as an example of a designation unit, an example of a notification unit including a liquid crystal display and a display as an example of a candidate notification unit 15 and an interface 16.

  At this time, the interface 16 is connected to the storage devices M1 to Mn, respectively, and enables data transmission / reception between the first data set DS1 to nth data set DSn and the main control unit 10.

  The main control unit 10 reads and executes a program or the like stored in advance in the ROM 12 based on an operation signal from the operation unit 14 corresponding to a user operation on the operation unit 14, thereby executing the above-described operation. It functions as a matching processing unit 10a and a totaling unit 10b. Data necessary for exhibiting the function in the main control unit 10 is temporarily stored in the RAM 11 and is read again as necessary to be used for exhibiting the function.

  On the other hand, the main control unit 10 (hereinafter simply referred to as the matching processing unit 10a) functioning as the matching processing unit 10a compares the tag information TG characterizing each of a plurality of question sentences as will be described in detail later. Thus, the identity (similarity) of the question sentence is determined. At this time, the dictionary data stored in the dictionary data storage unit 13 may be used for determining the identity as described later.

  Next, the main control unit 10 (hereinafter simply referred to as the totaling unit 10b) that functions as the totaling unit 10b executes the totaling process using the row data RD included in each data set DS as will be described in detail later. .

  Thus, as will be described later, the main control unit 10 considers the identity between the question sentences included in the different data sets DS based on the identity determined by the matching processing unit 10a, and the different data sets. For example, a list is displayed on the display 15 so that the aggregation results relating to the DS can be compared.

  Next, the aggregation processing according to the embodiment using the aggregation device S having the above-described configuration and the first data set DS1 to the nth data set DSn will be specifically described with reference to FIGS. .

  As the aggregation processing according to the embodiment, first, for example, the aggregation processing using the row data RD included in the first data set DS1 is executed using a conventional method (for example, the method described in Patent Document 1), and then The tabulation process using the row data RD included in the second data set DS2 to the nth data set DSn is executed while considering the identity with the question sentence included in the first data set DS1. After that, taking into account the sameness of the question texts, for example, a list of the aggregated results related to different data sets DS is displayed on the display 15 so as to be comparable.

  That is, as the aggregation process according to the embodiment, as shown in FIG. 3A, first, for example, the aggregation process using the row data RD included in the first data set DS1 is executed using a conventional method (step S10). Specifically, for example, as the processing of step S10, the counting unit 10b, based on the value of the row data RD included in the first data set DS1, the question sentence identification information IDQ included in the first data set DS1. The results of answering each question sentence identified by the above are aggregated, and the result is displayed on the display 15 for each item corresponding to each question sentence.

  Next, with respect to another data set DS (for example, the second data set DS2) different from the first data set DS1, the above-described totaling result (see step S10) for the first data set DS is reflected (more specifically, Includes a summation process (hereinafter referred to as “data” after a determination process (matching process) of identity as a question sentence with a question sentence included in the first data set DS1). It is confirmed whether or not an operation to execute (referred to as “crossing process” in the set DS) has been performed on the operation unit 14 (step S20).

  In the confirmation in step S20, when the operation is not performed (step S20; NO), each of the other second data set DS2 to n-th data set DSn is separately performed in the same manner as in step S10. The aggregation process using the raw data RD included in each is executed using a conventional method (step S100), the result is displayed on the display 15 (step S110), and the aggregation process according to the embodiment is terminated.

  On the other hand, when the operation unit 14 performs an operation to execute the crossing process of the data set DS in the confirmation in step S20, the matching processing unit 10a next outputs the first data set generated in step S10. The aggregation result for DS1 is acquired (step S30). Next, the matching processing unit 10a includes the question text and the first data set DS1 included in another data set DS that is a target of the crossing process (hereinafter, the other data set DS is referred to as a crossing target data set DS). The process of determining the identity between the question sentences included in each question sentence is performed for each question sentence included in the first data set DS1 by comparing the tag information TG characterizing each question sentence (step 1). S40). The process of step S40 will be described in detail later.

  Then, an item corresponding to the question sentence included in the crossing target data set DS after executing the process of determining the identity with the question sentence included in the first data set DS1 is generated / acquired (step S50). Further, for each of the acquired items, the answer results are totaled based on the value of the row data RD included in the crossing target data set DS (step S60), and the results are temporarily stored in, for example, the RAM 11 (step S60). Step S70). Here, in the process of step S50, the tabulation unit 10b includes items included in the first data set DS1 for items included in the crossing target data set DS and corresponding to the question sentence determined to have the same or similar. It is generated / acquired while referring to the question sentence determined as having the same identity. On the other hand, the items corresponding to the question texts included in the crossing target data set DS and determined to have no identity or similarity are generated regardless of the question texts included in the first data set DS1. /get.

  Next, the main control unit 10 performs the process of steps S40 to S70, and the crossing target data set on which the determination process such as the identity of the question sentence with the first data set DS1 and the aggregation process based on the determination process are executed. It is confirmed whether or not an operation for executing the crossing processing of the data set DS is performed on the data set DS other than the DS (for example, the third data set DS3) (step S80). ). When an operation for executing the crossing process is performed together with the designation of another data set DS to be subjected to the new crossing process (step S80; YES), the main control unit 10 returns to step S40. Then, the processes in steps S40 to S70 are performed on the other data set DS that is the target of the new crossing process.

  On the other hand, in the confirmation in step S80, when the operation to execute the crossing process of the data set DS is not performed (step S80; NO), the main control unit 10 then sequentially performs the operation of step S70 executed so far. The accumulated results stored and stored, for example, are displayed as a list on the display 15 so as to be mutually comparable for each data set DS in consideration of the identity of the question sentence (step S90), and then the aggregation process according to the embodiment is performed. finish.

  Next, the operation in step S40 will be described in detail with reference to FIG. 3B and FIG.

  In step S40, as shown in FIG. 3B, the matching processing unit 10a first sets a matching level to be described later for one question sentence (step S41), and then compares based on the set matching level. The tag information TG characterizing the target question sentence is compared with each other, and the identity of each is determined (step S42).

  Here, the operation of step S42 will be described with reference to FIG.

  As illustrated in FIG. 4A, as the operation of step S42, the same question sentence Qa identified by the question sentence identification information IDQa and one question sentence Qb identified by the question sentence identification information IDQb are the same. Assume that sex is determined. Here, tag information TG that characterizes the question sentence Qa includes tag information TGa-1 to tag information TGa-n, and tag information TG that characterizes the question sentence Qb includes tag information TGb-1 to tag information TGb-n. Suppose there is. In the comparison operation as step S42, as shown in FIG. 4A, the tag information TGa-1 and the tag information TGb-1 are identical, and the tag information TGa-2 and the tag information TGb-2 are identical. , Identity between tag information TGa-3 and tag information TGb-3, identity between tag information TGa-4 and tag information TGb-4, ..., identity between tag information TGa-n and tag information TGb-n Sex is determined independently. At this time, the dictionary data D1 to the dictionary data Dn corresponding to each combination of tag information TG are referred to as necessary for each determination.

  Here, the necessity of referring to the dictionary data D1 or the like is changed according to the matching level set in step S41. This matching level will be specifically described with reference to FIG. In FIG. 4B, “first tag” refers to a combination of tag information TGa-1 and tag information TGb-1 in the case illustrated in FIG. 4A, and “second tag” Similarly, it refers to a combination of tag information TGa-2 and tag information TGb-2. Similarly, the “nth tag” refers to a combination of nth tag information TGa-n that characterizes the question sentence Qa and nth tag information TGb-n that characterizes the question sentence Qb.

  The matching level is, for example, “synonymous (complete match)” as illustrated in FIG. 4B, depending on how strictly the degree of identity or similarity between question sentences to be compared is determined. ”,“ Similar level I ”,“ similar level II ”,“ similar level III ”, and“ similar level IV ”. This matching level is basically arbitrarily set according to the will of the user of the counting device S. For example, the number of data sets DS to be subjected to the crossing process or one data set DS Based on the number of included question sentences or the number of respondents to each question sentence, the counting device S can be configured to be automatically set.

  The contents of each matching level are specifically defined by the similarity between the tag information TGs that are compared in pairs. That is, as illustrated in FIG. 4B, when all the tags from the first tag to the nth tag are subjected to matching processing, and the contents are the same or synonymous in the dictionary data D1 to Dn (FIG. 4). 4 (b), indicated by “●”), the matching level is “synonymous (complete match)”. On the other hand, all the tags from the first tag to the fifth tag are subject to the matching process, and the contents are the same or synonymous in the dictionary data D1 to D5. In the case of “(×” in FIG. 4B), the matching level is “similarity level I”. In addition, the first tag and the fifth tag are subject to the matching process, and the contents are the same or synonymous in the dictionary data D1 to D5, and the third tag, the fifth tag, the sixth tag and the subsequent tags are all matched. If the second tag is similar to the second tag with reference to the corresponding dictionary data D2 (indicated by “◯” in FIG. 4B), the matching level is “similar level II”. " Similarly, as illustrated in FIG. 4B, the similarity level III and the similarity level IV are defined including a plurality of patterns.

  Based on the matching level set as described above (see step S41), the tag information TG characterizing one question sentence to be compared is compared with each other to determine the identity (step S42). In addition, the matching processing unit 10a confirms whether or not all of the tag information TGs to be compared (that is, the matching processing target) are the same (step S43). And when all the said is mutually the same (step S43; YES), the one question sentence compared at that time is assumed to be the same, and the said same question sentence contained in 1st data set DS1 The item corresponding to is automatically generated / acquired (step S44), and then the process proceeds to step S50 in FIG.

  On the other hand, if not all of the tag information TG to be compared in the confirmation in step S43 is the same as each other (step S43; NO), the matching processing unit 10a next selects the tag information of the traversing target data set DS. For each of the tag information TGs that are confirmed not to be the same among the TGs, for example, the tag information TG1 included in the first data set DS1 that seems to be similar to each other is displayed together with an indication that the user selects any one Are displayed on the display 15 as candidates (step S45). Thus, when any one of the candidates displayed on the display 15 is selected (step S46), the matching processing unit 10a compares the selected candidate tag information TG1 at that time. It is recognized as tag information TG1 included in the first data set DS1 that is the same as the tag information TG included in the traversing target data set DS. Thereby, the matching processing unit 10a confirms that the question text in the first data set DS1 including the tag information TG1 is the same as the question text in the crossing target data set DS to be compared, and the same The item corresponding to the question text is generated / acquired, and then the process proceeds to step S50 in FIG.

  Next, as a result of the execution of the operations of steps S10 to S80, the counting results displayed on the display 15 as the operation of step S90 will be described with reference to FIG.

  First, with respect to the first data set DS1 to the third data set DS3 according to the embodiment, when the respective aggregation processes are separately performed without executing the crossing process according to the embodiment, FIGS. ).

  More specifically, when the raw data RD included in the first data set DS1 is used, the number of samples (that is, the number of respondents) is calculated as a September 2008 questionnaire survey result on the question sentences Q1 to Q8. Suppose that the total result for each question Q is the total result L-DS1 illustrated in FIG.

  In addition, when the row data RD included in the second data set DS2 is used, the number of samples is 20,000 as a result of the questionnaire survey in September 2009 for the question sentences Q1 to Q15. Assume that the totaling result for L is the totaling result L-DS2 illustrated in FIG. In the example shown in FIG. 5B, the question sentences Q1 to Q15 do not follow the numbers and are in no particular order. However, the question sentences themselves must be in the same order among the data sets DS. It is an illustration of the absence. Needless to say, the count result L-DS2 may be displayed on the display 15 in the order of the numbers in the question sentences Q1 to Q15.

  Further, when the raw data RD included in the third data set DS3 is used, the number of samples is 22,000 as a result of the September 2010 questionnaire survey on the question sentences Q1 to Q11. Assume that the totaling result for L is the totaling result L-DS3 illustrated in FIG. In the example shown in FIG. 5C, as in the example shown in FIG. 5B, the question sentences Q1 to Q11 do not follow the numbers and are out of order, but this is shown in FIG. 5B. It is the same example as the case. Similarly, the total result L-DS3 may be displayed on the display 15 in the order of the numbers in the question sentences Q1 to Q11.

  Here, as illustrated in {} of FIG. 5D, the question sentence Q1 included in the first data set DS1 and the question sentence Q1 ′ included in the second data set DS2 are subjected to the above-described identity determination process. (See FIG. 3 (a) step S40). Similarly, the question sentence Q2 included in the first data set DS1 and the question sentence Q2 ′ included in the second data set DS2 can be regarded as the same or similar, and the question sentence Q4 included in the first data set DS1 The question sentence Q4 ′ included in the second data set DS2 can be regarded as the same or similar, and the question sentence Q6 included in the first data set DS1 and the question sentence Q6 ′ included in the third data set DS3 are the same. Or it can be considered similar. Further, the question sentence Q3 included in the first data set DS1, the question sentence Q3 ′ included in the second data set DS2, and the question sentence Q3 ″ included in the third data set DS3 can be regarded as the same or similar. Assume that the question sentence Q5 included in the first data set DS1, the question sentence Q5 ′ included in the second data set DS2, and the question sentence Q5 ″ included in the third data set DS3 can be regarded as the same or similar.

  When step S90 (see FIG. 3A) according to the embodiment is executed for the question sentence Q3 of the first data set DS1 in the above case, for example, the total result displayed on the display 15 is the second data set DS2. The question sentence Q3 ′ included in the question sentence Q3 ′ and the question sentence Q3 ″ included in the third data set DS3 are matched (shared) with the question sentence Q3 included in the first data set DS1, respectively. As shown in FIG. 4, the total results L-DS1 to L-DS3 of the respective data sets DS are the total results CL-DS123 reflected / aggregated for the question text Q3 of the first data set DS1.

  As described above, according to the operation of the aggregation device S according to the embodiment, the tag information TG and the corresponding row data RD are obtained based on the result of comparing the tag information TG between the different data sets DS. Calculate the aggregation result for each data set DS that is shared between the different data sets DS and that share the tag information TG and row data RD. Since the data sets DS are displayed in such a manner that they can be compared with each other, it is possible to easily recognize the survey results across these data sets DS having different survey items.

  Therefore, it is possible to effectively and easily recognize the survey results of different data sets DS and use them widely in activities such as advertisement creation.

  Furthermore, if the tag information TG and the raw data RD are repeatedly shared between the data sets DS, a desired survey result as a survey result across the data sets DS with different survey items can be easily and quickly acquired. can do.

  Further, since the tag information TG is shared based on the preset dictionary data D1 to Dn, more appropriate tag information TG can be shared based on an empirical rule.

  Furthermore, when the tag information TG to be shared is not the same, the tag information TG that becomes the tag information TG after the sharing is selected from the candidates for the tag information TG after the sharing. Even tag information TG that cannot be identical to each other can be shared. Even when the tag information TG cannot be automatically shared, the tag information TG can be manually shared.

(II) Modified Embodiment Next, a modified embodiment according to the present invention will be described.

(A) First Modification First, a first modification will be described with reference to FIG. FIG. 6 is a diagram illustrating a data structure and the like in the database according to the first modification.

  In the above-described embodiment, the tag information TG that characterizes each question sentence is configured to be set and stored / stored by the user in advance. However, other than this, the tag information TG is automatically set by the method illustrated in FIG. Tag information TG that characterizes each question sentence can also be generated.

  That is, as illustrated in FIG. 6A, the question sentence Qa identified by the question sentence identification information IDQa is divided into a plurality of words Wa-1 to Wa-n by a so-called morphological analysis method similar to the conventional technique. (Step S200). Then, for each of the divided words Wa-1 to Wa-n, the dictionary data (not shown) or the tag information database DB having the data structure illustrated in FIG. Tag information TG characterizing the question sentence Q including the word W is extracted, and the extracted tag information TG corresponds to the original word Wa-1 to the word Wa-n and characterizes the question sentence Qa. It is set as TGa-1 thru | or tag information TGa-n (step S210).

  At this time, as illustrated in FIG. 6B, the tag information database DB associates a single question sentence Q with a word W obtained by dividing the question sentence Q and tag information TG characterizing it. The tag information database DB stored and stored is preferably used.

  Further, as the operation of step S210, as in the embodiment, the question sentence Q divided into the words W that match each of the divided words Wa-1 to Wa-n is stored in the tag information database DB. In this case, the tag information TG that characterizes the stored question sentence Q may be used as it is as the tag information TGa that characterizes the original question sentence Qa. On the other hand, when the question sentence Q divided into all the matching words W is not stored in the tag information database DB, similar question sentences Q are extracted from the tag information database DB in descending order of similarity. It is preferable that they are configured to be displayed sequentially and to be selected by the user.

(B) Second Modification Next, a second modification will be described.

  With respect to the dictionary data D according to the embodiment (see FIG. 4A), every time one data set DS is newly stored, a word included in the question sentence Q included therein is automatically determined, so-called thesaurus. A dictionary may be used to automatically register synonyms or similar words as dictionary data D.

  Alternatively, the synonym or similar word information may be collected and automatically registered each time the user executes the aggregation process. In this case, if all of them are registered, a pattern registration that cannot be registered as a synonym or similar word is prepared so as to cope with the case where the number of extractions (hits) in the search increases too much, and this can be adjusted further. It can also be configured.

(C) Third Modification Next, a third modification will be described.

  For automatic adjustment of the pattern of matching processing (see FIG. 4B) according to the embodiment, the matching level may be freely set by the user for similar matching patterns. In addition, each time the user executes the aggregation process, the frequency adjustment may be automatically adjusted so that the frequently used pattern can be shared by the entire user as a preferential matching pattern.

(D) Fourth Modification A fourth modification will be described.

  In the operation of step S40 according to the embodiment (see FIG. 4), as described above, the determination process of the identity between the question sentence included in the crossing target data set DS and the question sentence included in the first data set DS1. Is executed “for each question sentence” included in the first data set DS1. As a result, in the example shown in FIG. 5E described above, only the tabulation result related to the common processing for one question sentence Q3 is displayed (see step S90 in FIG. 4).

  On the other hand, for example, if a combined question obtained by concatenating (synthesizing) all of the question sentences Q1 to Q8 related to the first data set DS is a question sentence, As a corresponding totaling result, a totaling result corresponding to that illustrated in FIG. 5D is displayed on the display 15. In this case, the question sentence Q1 ′, the question sentence Q2 ′, the question sentence Q3 ′, and the question sentence Q5 ′ included in the second data set DS2 are respectively included in the first data set DS1. , The question sentence Q3 ", the question sentence Q4 ', the question sentence Q5", and the question sentence Q6', which are matched (shared) with the question sentence Q3 and the question sentence Q5 and are included in the third data set DS3, respectively. It is matched with the question sentence Q3, question sentence Q4, question sentence Q5, and question sentence Q6 included in DS1. Then, regarding the total results of the second data set DS2 and the third data set DS3 corresponding to the question sentences Q1 to Q8 of the first data set DS1 illustrated in FIG. Will be displayed as a separate total result.

(E) Fifth Modification Finally, a fifth modification will be described.

  In the first data set DS1 described above, for example, if a combined question combining the question sentence Q1 and the question sentence Q3 included in the first data set DS1 is generated in the tabulation process, the second data set DS2 and the third data set DS3 correspond respectively. The tabulation results for the question sentence Q1 and the question sentence Q3 to be calculated can be automatically calculated. This is because when the aggregation process according to the embodiment is executed, the same question text can be mutually specified between different data sets DS. This is because the totaling result for the sentence can be automatically calculated as the totaling device S.

  Further, the program corresponding to the flowchart shown in FIG. 3 is recorded on a recording medium such as a flexible disk or acquired via a network such as the Internet, and these are read and executed by a microcomputer. The microcomputer can be used as the main control unit 10 according to the embodiment.

  As described above, the present invention can be used in the field of counting devices, and particularly when applied to the field of counting processing of questionnaire survey results, a particularly remarkable effect can be obtained.

DESCRIPTION OF SYMBOLS 10 Main control part 10a Matching process part 10b Total part 11 RAM
12 ROM
13 Dictionary Data Storage Unit 14 Operation Unit 15 Display 16 Interface S Aggregation Device DS1, DS2, DS3, DSn Data Set M1, M2, M3, Mn Storage Device RB Label Data RD Row Data DB Tag Information Database Qa, Qb Question Text D1, D2, D3, D4, Dn Dictionary data IDQa, IDQb Question identification information TGa-1, TGa-2, TGa-3, TGa-4, TGa-n, TGb-1, TGb-2, TGb-3, TGb- 4, TGb-n Tag information L-DS1, L-DS2, L-DS3, CL-DS123 Count result Wa-1, Wa-2, Wa-3, Wa-4, Wa-n Word

Claims (5)

An information processing apparatus for notifying tag information that characterizes a survey item and result information indicating a survey result for the survey item, each of which includes a plurality of data sets including the survey results,
Data set storage means for storing each of the data sets;
Comparison means for comparing the tag information included in each data set between the different data sets;
Based on the comparison result by the comparison unit, the tag information and the result information corresponding to the investigation item characterized by the tag information are shared by the data sets different from each other,
Using the tag information and the result information that have been shared, the tabulation unit that calculates the aggregation result for each of the data sets for which the tag information and the result information have been shared, for each data set;
A notifying means for notifying the calculated total results for each data set in which the tag information and the result information are made common to each other in such a manner that the data sets can be compared with each other;
Equipped with a,
The common means is:
Candidate storage means for storing candidate tag information that is a candidate for the tag information after sharing;
An extraction means for extracting the candidate tag information related to the commonization from the stored candidate tag information when the tag information to be shared is not the same;
Candidate notification means for notifying the extracted candidate tag information;
Selection means used for selecting the candidate tag information to be the tag information after sharing from the extracted candidate tag information;
The information processing apparatus according to claim Rukoto equipped with. The information processing apparatus according to claim 1,
The common means is:
Comprising dictionary information storage means for storing at least one of identity or similarity between the tag information to be shared and storing preset dictionary information;
An information processing apparatus, wherein the tag information is shared based on the stored dictionary information. The information processing apparatus according to claim 1 ,
The information processing apparatus according to claim 1, wherein the sharing unit includes a specifying unit used to specify the tag information to be shared and the tag information after sharing . An information processing apparatus for notifying tag information that characterizes a survey item, and result information indicating a survey result for the survey item, each of which includes a plurality of data sets, and that includes a selection unit. Included computers,
Data set storage means for storing each of the data sets;
Comparison means for comparing the tag information included in each data set between the different data sets,
Based on the comparison result by the computer functioning as the comparison unit, the tag information and the result information corresponding to the investigation item characterized by the tag information are shared between the different data sets. means,
Using the tag information and the result information that have been shared, the tabulation unit that calculates the tabulation result for each of the data sets for which the tag information and the result information have been shared, for each data set, and
Notification control means for controlling the notification means so as to notify the calculated total results for each data set in which the tag information and the result information are made common to each data set;
An information processing program that functions as
The computer that functions as the common means;
Candidate storage means for storing candidate tag information that is a candidate for the tag information after sharing,
An extraction means for extracting the candidate tag information related to the commonization from the stored candidate tag information when the tag information to be shared is not the same; and
Candidate notification control means for notifying the candidate notification means of the extracted candidate tag information,
Function as
The information processing apparatus program , wherein the selection means is used to select the candidate tag information to be the tag information after sharing from the extracted candidate tag information . An information processing device for notifying tag information that characterizes a survey item and result information indicating a survey result for the survey item, each of which includes a plurality of data sets, and storing each of the data sets An information processing method executed in an information processing apparatus including a data set storage unit, a candidate storage unit, and a selection unit,
A comparison step of comparing the tag information included in each data set between the different data sets;
Based on the comparison result in the comparison step , the tag information and the result information corresponding to the investigation item characterized by the tag information, a common step for sharing the different data sets,
Using the tag information and the result information that have been shared, the tabulation process for calculating the aggregation result for each of the data sets for which the tag information and the result information have been shared, for each data set;
A notification step of notifying the calculated total results for each of the data sets in which the tag information and the result information are made common so that the data sets can be compared with each other;
Including
The candidate storage means stores candidate tag information that is a candidate for the tag information after sharing,
The commonization step includes
When the tag information to be shared is not the same, an extraction step of extracting the candidate tag information related to the commonization from the stored candidate tag information;
A candidate notification step of notifying the extracted candidate tag information;
Including
The information processing method , wherein the selection unit is used to select the candidate tag information to be the tag information after sharing from the extracted candidate tag information .

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