JP7540230B2 - Information processing program, information processing method, and information processing device - Google Patents

Description

The present invention relates to an information processing program, an information processing method, and an information processing device.

In recent years, application work using a personal computer (PC) is frequently performed in office clerical work. Therefore, in order to improve the efficiency of office work, it is desirable to improve the efficiency of application work using a PC. Therefore, one possible method for improving application work using a PC is to classify tasks using a PC, analyze the processes performed in the application work, identify the tasks or processes that are bottlenecks, and improve the efficiency of the identified tasks or processes.

In this way, when identifying a series of tasks or processes to improve PC-based application procedures, it is necessary to consider tasks within a single task that may involve tasks using multiple windows as a single task.

Conventional technology for recording work done on a PC includes a technique for saving a log of the names of windows that are active on the PC and the amount of time they are active. With this technique, each window is recorded as a single task. For example, tasks performed in different windows are recognized as different tasks. Also, if you close the window you were working in and then reopen the same window to continue working, the tasks before and after closing the window are recognized as different tasks.

There is also a conventional technology that records business operations performed using a terminal, groups operations that are presumed to be operations for the same case based on criteria such as from login to logout, or on pre-associated tasks or time differences, and creates a log. There is also a conventional technology that collects and analyzes work logs using the on/off of a PC's power, the time spent using IP telephone tools, IP conferencing tools, and email tools, and schedule data. There is also a conventional technology that associates the logs of multiple business applications in a table classified by item, saves them, and analyzes them.

JP 2018-136636 A JP 2006-195777 A JP 2011-221861 A

However, in conventional technology that collects work logs for each active window, related work performed using different windows within a single task is managed as separate tasks. Furthermore, the log is the same when a task is completed and the window used for the task is closed as when the task window is switched to processing using a different active window without closing it. In this way, since the start and end times when the window was kept active are recorded, it is difficult to determine whether the task using that window has finished or is still ongoing. Therefore, it is difficult to view the tasks included in a single task as a single task, and it is difficult to identify application tasks performed using a PC and improve the efficiency of the task.

It is possible to have a human determine and associate related tasks based on the window names and temporal relationships contained in the log history, but the criteria are vague, making the association difficult and difficult to implement. Also, if one task is counted for each active window, an action is recorded every time the window is switched, which could result in an enormous number of recorded tasks, increasing the workload and placing a heavy burden on the worker in the task of sorting.

In addition, in conventional technologies that record business operations performed using a terminal and group them based on pre-associated tasks or time differences, the burden of registering related tasks is high and tasks that are consecutive in time are not necessarily related, making it difficult to group related tasks together. In conventional technologies that collect task logs using PC power on/off, various tools, and schedule data, it is difficult to determine whether tasks are related or not. In conventional technologies that classify and save logs of multiple business applications by item, related tasks are extracted and classified in advance, which places a heavy burden on the worker and makes it difficult to group related tasks together. Therefore, regardless of which conventional technology is used, it is difficult to identify and extract application tasks using a PC, and it is difficult to improve business efficiency.

The disclosed technology has been developed in consideration of the above, and aims to provide an information processing program, an information processing method, and an information processing device that improve business efficiency.

In one aspect of the information processing program, information processing method, and information processing device disclosed in the present application, a computer is caused to execute the following processes. Based on keywords extracted from each of a plurality of active windows, a classification tag representing the task among a plurality of tasks corresponding to each of the tasks is assigned to each of a plurality of tasks performed using each of the windows. Based on the start and end points of the task identified based on the tasks, and the type of the classification tag, a plurality of tasks are extracted for each of the tasks. Information on the extracted tasks for each of the tasks is grouped and recorded.

In one aspect, the present invention can improve business efficiency.

FIG. 1 is a block diagram of a work information management server according to a first embodiment. FIG. 2 is a diagram showing the transition of processes when applying for a product purchase. FIG. 3 is a diagram illustrating an example of the work information database. FIG. 4 is a diagram illustrating an example of the process database. FIG. 5 is a diagram illustrating an example of a temporary file. FIG. 6 is a diagram illustrating an example of a confirmation screen for related tasks in one application task according to the first embodiment. FIG. 7 is a diagram showing an example of a confirmation screen when a deletion target is selected. FIG. 8 is a diagram illustrating an example of the task classification database. FIG. 9 is a diagram showing the process transition when applying for travel expenses. FIG. 10 is a flowchart of a task classification process performed by the task information management server according to the first embodiment. FIG. 11 is a block diagram of a work information management server according to the second embodiment. FIG. 12 is a diagram illustrating an example of a confirmation screen according to the second embodiment. FIG. 13 is a diagram showing an example of a confirmation screen for prompting selection of the display of the skipping work. FIG. 14 is a diagram showing an example of a confirmation screen on which an omitted task is additionally displayed. FIG. 15 is a flowchart of a task classification process performed by the task information management server according to the third embodiment. FIG. 16 is a block diagram of a work information management server according to the fourth embodiment. FIG. 17 is a flowchart of management of the task classification database using the frequency of use by the task information management server according to the fourth embodiment. FIG. 18 is a flowchart of another example of management of the task classification database using the frequency of use. FIG. 19 is a flowchart of a window display process using the frequency of use in application work. FIG. 20 is a diagram showing a system configuration in which a plurality of worker terminals are connected. FIG. 21 is a hardware configuration diagram of the work information management server.

Below, examples of the information processing program, information processing method, and information processing device disclosed in the present application are described in detail with reference to the drawings. Note that the information processing program, information processing method, and information processing device disclosed in the present application are not limited to the following examples.

FIG. 1 is a block diagram of a work information management server according to a first embodiment. A worker terminal 2 is connected to the work information management server 1. The worker terminal 2 is, for example, a personal computer. A worker uses the worker terminal 2 to perform various office tasks, such as application procedures.

The worker terminal 2 has a display control unit 21 and a process execution unit 22. The display control unit 21 displays a work screen represented as a window on a display device such as a monitor (not shown). The worker uses an input device such as a keyboard or mouse (not shown) to input information while referring to the display device. The process execution unit 22 executes processes for various tasks using input information from the input device. The process execution unit 22 then issues a display instruction to the display control unit 21 to display a work screen such as an input screen or a result display screen.

The display control unit 21 transmits information about each active window displayed on the display device to the work information management server 1. The information about each window includes an icon representing the window, the window title, the reference URL (Uniform Resource Locator), start time, end time, usage time, and the state of the application when working with that window.

The process execution unit 22 also transmits information about the process executed when performing each application task to the work information management server 1. The process information sent to the work information management server 1 may be information about the process executed when each application task is executed individually and collectively in advance on a trial basis. Alternatively, the process information sent to the work information management server 1 may be information about the process executed when the actual application task is performed on the worker terminal 2. The process information includes, for example, the window title, the reference URL, the process contents, and the application status in the process.

As an example, the process transition when applying for a product purchase will be described with reference to FIG. 2. FIG. 2 is a diagram showing the process transition when applying for a product purchase.

When a worker starts work using the worker terminal 2, the process execution unit 22 starts the work by opening an application window used for the application work of the product purchase (process P1). Then, as the worker works using the worker terminal 2, the process execution unit 22 executes various processes for the application (process P2). When performing process P2, information on the application work window displayed on the display device by the display control unit 21 is sent to the work classification processing unit 10.

When the worker performs product research, the process execution unit 22 receives instructions from the worker and opens a window for product research to perform the product research (process P3). When performing process P3, information on the window for product research displayed on the display device by the display control unit 21 is sent to the task classification processing unit 10.

When a worker performs processes such as writing purchased products into the budget ledger or checking the remaining budget, the process execution unit 22 opens a window for the budget ledger and performs budget ledger management (process P4). When performing process P4, the information of the window for the budget ledger displayed on the display device by the display control unit 21 is transmitted to the work classification processing unit 10.

Upon receiving instructions from the worker, the process execution unit 22 proceeds with the product purchase application process by going through processes P2, P3, and P4. Furthermore, for example, if the worker interrupts the application process, the process execution unit 22 saves the work content at that time in a storage device (not shown) (process P5). Then, the process execution unit 22 temporarily suspends the product purchase application process (process P6). Thereafter, when the worker resumes the product purchase application process, the process execution unit 22 returns to process P2.

When the worker completes the application process for purchasing the product, the process execution unit 22 performs a process to complete the application, such as executing the application (process P7). In this case, when process P7 is performed, the display control unit 21 transmits information about a window for completing the application to the task classification processing unit 10. Thereafter, the process execution unit 22 ends the application process for purchasing the product (process P8).

Next, returning to FIG. 1, the work information management server 1 will be described. As shown in FIG. 1, the work information management server 1 has a work classification processing unit 10, a data storage unit 11, an input/output device 12, an input/output processing unit 13, and an analysis unit 14.

The data storage unit 11 is a storage device. The data storage unit 11 has a work information database 111, a temporary file 112, a process database 113, and a work classification database 114.

Figure 3 is a diagram showing an example of a work information database. The work information database 111 is a database in which classification tag information is registered in correspondence with keywords. The medium classification items shown in Figure 3 correspond to the classification tag information. Here, a keyword is a word that represents the characteristics of the work content performed using a window to identify the window used in the work. Keywords are extracted from the title and main text. Classification tag information is information for classifying work by application business. This work information database is an example of "correspondence information".

The temporary file 112 is a file that temporarily stores information about tasks performed in each window. As shown in FIG. 2, the temporary file 112 registers information in which classification tags have been added to task information collected by the task classification processing unit 10.

Figure 4 shows an example of a process database. The process database 113 stores information on the processes executed for each application task executed by the processing execution unit 22 in the worker terminal 2. In other words, the process information is related work information that represents the work to be performed for each application task.

For example, when each application process is individually and collectively executed by the process execution unit 22 on a trial basis, the process executed for each application process is stored in the process database 113. Also, for example, in the case of a configuration in which the process executed when the actual application work is performed on the worker terminal 2 is sent, the sent process may be accumulated and learned, and the process extracted for each work may be stored in the process database 113. As shown in FIG. 3, the process database 113 stores window titles, reference URLs, and the like. Also, the contents of each process are registered in the process item in the process database 113 in FIG. 3. Also, the application state in the process is registered in the small classification in the process database 113 in FIG. 3. Furthermore, in the medium classification, classification tag information corresponding to the title similar to the contents registered in the work information database 111 is registered. Here, in this embodiment, the title of the window is registered in the process database 113, but this is not limited to this, and other information may be registered as long as it represents the work content performed in the window.

The task classification database 114 is a database in which information on tasks classified by application tasks is registered. As shown in FIG. 2, the task classification processing unit 10 registers information in the task classification database 114 in which tasks for each window are classified by application tasks using information stored in the temporary file 112. By referring to the information registered in this task classification database 114, it is possible to identify and extract a group of related tasks for each application task.

The task classification processing unit 10 classifies various tasks performed using windows on the worker terminal 2 by application task. As shown in FIG. 1, the task classification processing unit 10 has a task information collection unit 101, a text extraction unit 102, a tagging unit 103, a listing unit 104, a verification management unit 105, a grouping unit 106, and a window management unit 107.

The work information collection unit 101 receives information about active windows that the display control unit 21 has displayed on the display device of the worker terminal 2, and collects it as work information. As described above, the window information includes an icon representing the window, a title, a URL, a start time, an end time, a usage time, and the state of an application when working using the window. The work information collection unit 101 outputs the collected work information to the text extraction unit 102.

The text extraction unit 102 receives input of work information from the work information collection unit 101. Next, the text extraction unit 102 acquires the title and URL of each window from the information of each window included in the work information. The text extraction unit 102 then extracts text representing the content of the work to be performed using that window from the title and URL as a keyword. The text extraction unit 102 then outputs the work information together with the extracted keywords to the tag assignment unit 103.

The tagging unit 103 receives input of the work information and keywords for each window extracted by the text extraction unit 102 from the text extraction unit 102. Next, the tagging unit 103 searches the work information database 111 to obtain classification tag information corresponding to the keywords extracted by the text extraction unit 102. Next, the tagging unit 103 obtains the start time, end time, and usage time of the window, and the state of the application during the work using the window, from the window information.

Then, the tagging unit 103 generates the temporary file 112 shown in FIG. 5. FIG. 5 is a diagram showing an example of a temporary file. The tagging unit 103 registers the icon of the window in the temporary file 112, and also registers the keywords extracted by the text extraction unit 102 in the temporary file 112. Next, the tagging unit 103 registers the start time, end time, and usage time in the temporary file 112. Furthermore, the tagging unit 103 registers classification tag information corresponding to the keywords in the temporary file 112 as a medium classification. This allows the tagging unit 103 to add classification tag information representing the business to which the work corresponds to the work performed using each window to the work performed using the window. In addition, the tagging unit 103 registers the state of the application during the work using the window as a small classification in the temporary file 112. Each time a work using a window is performed, the tagging unit 103 sequentially registers information on the work performed using the window in the temporary file 112, and adds classification tag information to the information on the work performed for each window and accumulates it.

The list-up unit 104 identifies the task that triggers the start of the application task from the series of tasks executed in each application task stored in the process database 113. For example, if the title of a window is "Start Purchase Application", the list-up unit 104 can identify the task performed using that window as the task that triggers the start of the application task. The list-up unit 104 then determines whether the task that triggers the start of the application task has been registered in the temporary file 112, and determines whether the application task has been started. The list-up unit 104 then monitors the tasks registered in the temporary file 112, and detects the task that completes the application task from among the tasks that follow the task that starts the application task. For example, if the title of a window is "Request for Approval", the list-up unit 104 detects the task performed using that window as the task that completes the application task.

When the list-up unit 104 detects an operation that completes the application process, it reads out the accumulated information on the operation for each window from the temporary file 112. Here, the list-up unit 104 may read out the information on the operation a certain time after the application process is completed. Then, the list-up unit 104 extracts, from the read information on the operation for each window, those that have matching classification tag information as related operations.

Next, the list-up unit 104 refers to information on a series of processes executed in each application task stored in the process database 113. Next, the list-up unit 104 identifies application tasks that have the same classification tag as the extracted task and whose work content in each process matches. Then, if the extracted tasks include work performed in a process in an application task other than the identified application task, the list-up unit 104 deletes that work from the extracted tasks. This allows the list-up unit 104 to remove work performed in other application tasks as noise from the extracted related tasks.

Furthermore, the list-up unit 104 checks the process in the identified application task and identifies the task that triggers the start of the application. Next, the list-up unit 104 detects a task that matches the identified task that triggers the start of the application from among the extracted related tasks, and identifies the time when that task was performed as the start time of the application task. Next, the list-up unit 104 detects a task that completes the application from among the tasks that follow the task that starts the application, and identifies the time when that task was performed as the end time of the application task. Then, the list-up unit 104 identifies from the extracted tasks the tasks that are from a task that is a predetermined time before the start time of the application to a task that is a predetermined time after the end time of the application task, and sets these as related tasks in one application task. After that, the list-up unit 104 outputs information on the related tasks in one identified application task to the verification management unit 105.

The verification management unit 105 receives input of information on related tasks in one application transaction from the list-up unit 104. Next, the verification management unit 105 generates a confirmation screen 201 shown in FIG. 6 that displays a list of related tasks in one application transaction. FIG. 6 is a diagram showing an example of a confirmation screen for related tasks in one application transaction related to Example 1.

The verification management unit 105 generates a list of related tasks, for example, by arranging icons indicating windows used in each task and the titles of those windows. Furthermore, the verification management unit 105 adds highlighting 211 to surround tasks included in the related tasks in the list. At this point, all tasks extracted by the listing unit 104 are considered to be related tasks, so the verification management unit 105 surrounds all tasks in the list with highlighting 211. Furthermore, the verification management unit 105 highlights tasks considered to be related tasks by changing the background color or pattern.

The verification management unit 105 also adds a selection field that allows the user to select whether or not to exclude each task in the list. The verification management unit 105 also adds the window usage time for each task displayed in the list to calculate a total task time, and adds this to the confirmation screen 201. The verification management unit 105 also adds a button to the confirmation screen 201 for registering the determined content as a related task in one application task. The verification management unit 105 then outputs the generated confirmation screen 201 to the input/output processing unit 13, and causes the input/output device 12 to display the confirmation screen 201 shown in FIG. 6. As a result, the verification management unit 105 requests the worker to confirm whether the correspondence between the tasks and the business is correct.

Then, if the selection field for the deletion target is checked by the worker as a result of the correctness check, the verification management unit 105 removes the selected work from the related work. FIG. 7 is a diagram showing an example of a confirmation screen when a deletion target is selected. For example, as shown in FIG. 7, when a selection field is checked, the verification management unit 105 removes the checked work from the related work and generates a confirmation screen 202 that displays a highlight 212 surrounding the related work excluding the selected work. In this case, if there is a work in the list that can be removed from the range of the highlight 212 by shrinking the frame, the verification management unit 105 shrinks the frame to emphasize that it is not included in the related work. Furthermore, the verification management unit 105 changes the background of the related work to highlight it. Then, the verification management unit 105 outputs the newly generated confirmation screen 202 according to the worker's selection to the input/output processing unit 13, and causes the input/output device 12 to display the confirmation screen 202 shown in FIG. 7.

Then, when the worker presses a button to register this content and the related tasks in one application transaction are confirmed, the verification management unit 105 outputs information about the tasks confirmed as related tasks in one application transaction to the grouping unit 106.

The grouping unit 106 receives input of information on tasks that have been determined to be related tasks in one application task from the verification management unit 105. The grouping unit 106 then identifies the major classification of the application task of the related tasks from the information on each task. Furthermore, the grouping unit 106 acquires information on the medium and small classifications of each task, the start time, the end time, and the file path of the window used for the task from the information on each task. The grouping unit 106 then uses the acquired information to group related tasks for each application task into a group and registers the information shown in FIG. 8 in the task classification database 114. FIG. 8 is a diagram showing an example of the task classification database. By registering related tasks in each application task as a group in this way, the grouping unit 106 makes it easy to find the time required for the entire application task and the time required for each task in the application task. This makes it easy to perform bottleneck analysis in the application task.

After the grouping unit 106 has completed registration in the task classification database 114, the update unit 109 acquires information about each task registered by the grouping unit 106. Next, the update unit 109 acquires keywords for each task registered in the task classification database 114 from the information about each task. Next, the update unit 109 compares the keywords registered in the task classification database 114 with keywords already registered in the task information database 111. Then, the update unit 109 determines whether or not there is a new keyword that is not registered in the task information database 111 among the keywords for each task registered in the task classification database 114. If a new keyword is present, the update unit 109 registers the new keyword and the corresponding subcategory information in the task information database 111 and updates it.

Here, Figure 2 shows an example of an application for product purchase, but other application tasks can also be classified in the same way. Figure 9 shows the process transition when applying for travel expense settlement. The process transition of the travel expense settlement application task will be explained with reference to Figure 9.

When the worker starts working using the worker terminal 2, the process execution unit 22 starts the work by opening an application window used for the business trip settlement application work (process P11). Then, as the worker works using the worker terminal 2, the process execution unit 22 executes various processes for the business trip settlement application (process P12). When performing process P12, information on the window for the business trip settlement application work displayed on the display device by the display control unit 21 is sent to the work classification processing unit 10.

When the worker investigates travel expenses and the location of the business trip destination, the process execution unit 22 receives an instruction from the worker and opens a window for investigation and investigates the travel expenses and the location (process P13). When process P13 is performed, the information of the investigation window displayed on the display device by the display control unit 21 is transmitted to the task classification processing unit 10.

Upon receiving instructions from the worker, the process execution unit 22 advances the business trip settlement application process by executing processes P12 and P13. Furthermore, for example, if the worker interrupts the business trip settlement application process, the process execution unit 22 saves the work content at that time in a storage device (not shown) (process P14). Then, the process execution unit 22 temporarily suspends the business trip settlement application process (process P15). Thereafter, when the worker resumes the business trip settlement application process, the process execution unit 22 returns to process P12.

When the worker completes the travel expense claim process, the process execution unit 22 performs a process to complete the claim, such as executing the travel expense claim (process P16). In this case, when process P16 is performed, the display control unit 21 sends information about a window for completing the travel expense claim to the task classification processing unit 10. Thereafter, the process execution unit 22 ends the travel expense claim process (process P17).

In this case too, the work classification processing unit 10 acquires information on the work performed in the business trip settlement application process and information on the work performed before and after that, adds classification tag information, and stores the information in the temporary file 112. The work classification processing unit 10 then uses the information stored in the temporary file 112 to register in the work classification database 114 tasks related to the business trip settlement application process as a group. In this way, the work classification processing unit 10 can register in the work classification database 114 tasks related to various application processes, not limited to application processes for product purchases, as a group. Therefore, information on tasks related to various application processes can be used for analysis.

For example, the analysis unit 14 illustrated in FIG. 1 obtains information on related tasks for each application task from the task classification database 114. Then, the analysis unit 14 calculates the total time required for each application task and identifies the application task that took the longest time. The analysis unit 14 also identifies the task that takes the longest time among the related tasks in each application task and obtains that time. Then, the analysis unit 14 determines that the application task that took the longest time or the task that takes the longest time in each application task will be a bottleneck, and notifies the input/output processing unit 13 of the determination result to display it on the input/output device 12. The analyst can identify the bottleneck by checking this analysis result using the input/output device 12. The analyst can also easily perform bottleneck analysis himself by referring to the information registered in the task classification database 114.

Next, the flow of the task classification process by the task information management server 1 according to the present embodiment will be described with reference to FIG. 10. FIG. 10 is a flowchart of the task classification process by the task information management server according to the first embodiment.

The worker starts up the worker terminal 2 (step S1).

The work information collection unit 101 acquires information about the active window from the display control unit 21 of the worker terminal 2 and collects work information (step S2). The work information collection unit 101 outputs the collected work information to the text extraction unit 102.

The text extraction unit 102 receives the work information as an input from the work information collection unit 101. Next, the text extraction unit 102 extracts text representing the content of the work performed using each window from the title and URL of each window included in the work information as a keyword (step S3). The text extraction unit 102 then outputs the work information together with the extracted keywords to the tag assignment unit 103.

The tagging unit 103 receives input of the work information and the keywords for each window extracted by the text extraction unit 102 from the text extraction unit 102. Next, the tagging unit 103 searches the work information database 111 to obtain classification tag information corresponding to the keywords, determines the classification tag for each work, and saves the information of each work to which the classification tag has been assigned in a temporary file 112 (step S4).

The list-up unit 104 uses the information on the tasks that trigger the start of each application task registered in the process database 113 to determine whether application processing has started (step S5). If application processing has not started (step S5: No), the task classification process returns to step S2 and repeats the acquisition of task information for the previous tasks.

In contrast, if the application process has started (step S5: Yes), the list-up unit 104 starts judging whether the application process has been completed (step S6) to confirm the completion of the application process. If the application process has not been completed (step S6: No), the task classification process returns to step S2 and repeats the acquisition of task information during the execution of the application task.

When the application process is completed (step S6: Yes), the list-up unit 104 extracts related tasks in one application task from the temporary file 112 using the classification tag information and the process database 113 (step S7). Then, the list-up unit 104 outputs information on the extracted related tasks to the verification management unit 105.

The verification management unit 105 generates a confirmation screen that allows the user to select the tasks to be excluded. The verification management unit 105 then outputs the generated confirmation screen to the input/output processing unit 13, and causes the input/output device 12 to display it (step S8).

Then, the verification management unit 105 acquires the information input by the worker using the input/output device 12 and verifies the accuracy (step S9). At this time, if there is any work to be excluded from the application work, the worker selects the work to be excluded and notifies the verification management unit 105. When the related work in the application work is confirmed, the worker presses the registration button. When the registration button is pressed, the verification management unit 105 judges the excluded work to be incorrect and the remaining work to be correct, verifies the accuracy, confirms the work as related work to the application work, and outputs information on the confirmed related work to the grouping unit 106.

The grouping unit 106 receives input of information on related tasks from the verification management unit 105. The grouping unit 106 then compiles the related tasks for one application task and stores them in the task classification database 114 (step S10).

The update unit 109 acquires task keywords stored in the task classification database 114. The update unit 109 then determines whether or not the acquired keywords include new keywords that are not included in the keywords registered in the task information database 111 (step S11). If no new keywords exist (step S11: No), the task classification process ends.

On the other hand, if a new keyword is present (step S11: Yes), the update unit 109 adds and stores the new keyword and its corresponding classification tag in the work information database 111 (step S12). Then, the work classification process ends.

As described above, the work information management server of this embodiment generates and stores a database in which related tasks are categorized for each application task. This makes it easy to view the tasks included in one application task as a single task, and makes it easy to identify and extract a series of tasks related to the application task. Therefore, bottleneck analysis of application tasks can be easily performed, making it possible to improve work efficiency.

Figure 11 is a block diagram of a work information management server according to Example 2. The work information management server 1 according to this example differs from Example 1 in that it is possible to automatically open a window used in a task related to a specific application task when the specific application task is started. As shown in Figure 11, the work information management server 1 according to this example has a window management unit 107 in addition to the units exemplified in Example 1. In the following explanation, the operation of each unit similar to that of Example 1 will be omitted.

As shown in FIG. 12, the verification management unit 105 generates a confirmation screen 203 having a list of related tasks and, as registration buttons, buttons 231 and 232 for selecting whether or not to automatically open a window used in a task related to this application task in the next application. FIG. 12 is a diagram showing an example of a confirmation screen according to the second embodiment. Automatically opening a window means, for example, that if the window is a site on a network, that site is opened. The verification management unit 105 outputs the generated confirmation screen 203 to the input/output processing unit 13.

The input/output processing unit 13 causes the input/output device 12 to display a confirmation screen 203 having buttons 231 and 232 shown in FIG. 12.

The worker refers to the confirmation screen, selects the task to be deleted, etc., and then when the task related to the target application task is confirmed, presses button 231 or 232 to instruct the registration of the task related to the target application task. Here, if the worker wants to open the window used in the related task the next time a similar application task is performed, he/she selects button 231. Conversely, if the worker does not want to open the window used in the related task the next time a similar application task is performed, he/she selects button 231.

The input/output processing unit 13 receives input from the input/output device 12 of information on whether button 231 or button 232 was selected, along with an instruction to register a related task. When button 231 is selected, the input/output processing unit 13 notifies the verification management unit 105 of a registration instruction and instructs the window management unit 107 to automatically expand the site when a similar application task is performed. When button 232 is selected, the input/output processing unit 13 notifies the verification management unit 105 of a registration instruction. In that case, the input/output processing unit 13 does not notify the window management unit 107 of the automatic expansion of the site when a similar application task is performed.

When button 231 is pressed when registering a task related to an application task, the window management unit 107 receives an instruction from the input/output processing unit 13 to automatically expand the site when the same application task is performed. The window management unit 107 then stores the type of application task for which automatic site expansion was instructed.

The window management unit 107 receives notification of information on the process to be executed from the process execution unit 22. The window management unit 107 then checks whether the notified process is a task to start an application task for which automatic site expansion is instructed. If the notified process is a task to start an application task for which automatic site expansion is instructed, the window management unit 107 acquires tasks related to the application task from the task classification database 114. The window management unit 107 then instructs the display control unit 21 of the worker terminal 2 to expand a window to be used in the acquired task.

As described above, the work information management server according to this embodiment can automatically open on the worker's terminal the window to be used for the registered related work when performing an application task for which related work is registered. As a result, when a worker performs a similar application task, the window to be used for that application task automatically opens when the worker starts the task, enabling the worker to efficiently perform the application task.

Next, Example 3 will be described. The work information management server according to this example differs from Example 1 in that it allows the worker to add additional work selected by the worker to the work related to a specific application task. The work information management server according to this example is also represented by the block diagram of FIG. 1. In the following explanation, the operation of each part similar to that of Example 1 will be omitted.

The verification management unit 105 according to this embodiment generates a confirmation screen 204 to which confirmation information 241-243 is added, which asks whether or not to display the omitted tasks that have been omitted from the tasks related to the target application task, as shown in FIG. 13. FIG. 13 is a diagram showing an example of a confirmation screen that prompts the user to select whether or not to display the omitted tasks. Selection buttons are attached to the confirmation information 241-243. The verification management unit 105 then outputs the confirmation screen 204 to which the confirmation information 241-243 has been added to the input/output processing unit 13, which then displays the confirmation screen 204 on the input/output device 12. Hereinafter, when the confirmation information 241-243 is not differentiated, it is referred to as confirmation information 240.

When the worker uses the input/output device 12 to press the selection button for any one or a combination of pieces of confirmation information 240, the verification management unit 105 receives the information of the confirmation information 240 for which the confirmation button was pressed from the input/output processing unit 13. The verification management unit 105 then displays the missing task corresponding to the confirmation information 240 for which the selection button was pressed in a list of related tasks.

For example, a case will be described where the selection buttons for confirmation information 242 and 243 on confirmation screen 204 are pressed. In this case, the verification management unit 105 displays the missing tasks indicated by confirmation information 242 and 243 in a list, as shown on confirmation screen 205 in FIG. 14. FIG. 14 is a diagram showing an example of a confirmation screen on which the missing tasks are additionally displayed. In this case, the verification management unit 105 deletes confirmation information 242 and 243 from the screen. Furthermore, the verification management unit 105 adds an item for selecting whether or not to include the displayed missing tasks in related tasks, as shown in the next use item on confirmation screen 205.

In this embodiment, the verification management unit 105 provides a check box for the next use item for the tasks extracted in the list unit 104 as related tasks as shown in FIG. 14, but this box does not have to be provided. Also, in FIG. 14, a check box is provided for the displayed missing tasks to determine whether or not they should be excluded, and the missing tasks can be checked for exclusion if they are not required. However, the verification management unit 105 may generate a confirmation screen 205 so that the missing tasks are excluded if the next use item is not checked.

When the verification management unit 105 receives a registration instruction, it removes the tasks that have been excluded from the related tasks and includes the missing tasks for which the next use item has been checked into the related tasks, thereby determining the related tasks of the application task. The verification management unit 105 then outputs information on the determined related tasks of the application task to the grouping unit 106.

Next, the flow of the task classification process by the task information management server 1 according to the present embodiment will be described with reference to FIG. 15. FIG. 15 is a flowchart of the task classification process by the task information management server according to the third embodiment.

The worker starts up the worker terminal 2 (step S101).

The work information collection unit 101 acquires information about the active window from the display control unit 21 of the worker terminal 2 and collects work information (step S102). The work information collection unit 101 outputs the collected work information to the text extraction unit 102.

The text extraction unit 102 receives the work information as an input from the work information collection unit 101. Next, the text extraction unit 102 extracts text representing the content of the work to be performed using each window from the title and URL of each window included in the work information as a keyword (step S103). The text extraction unit 102 then outputs the work information together with the extracted keywords to the tag assignment unit 103.

The tagging unit 103 receives input of the work information and keywords for each window extracted by the text extraction unit 102 from the text extraction unit 102. Next, the tagging unit 103 searches the work information database 111 to obtain classification tag information corresponding to the keywords, determines the classification tag for each work, and saves the information of each work to which the classification tag has been assigned in a temporary file 112 (step S104).

The list-up unit 104 uses the information on the tasks that trigger the start of each application task registered in the process database 113 to determine whether application processing has started (step S105). If application processing has not started (step S105: No), the task classification process returns to step S102 and repeats the acquisition of task information for the previous tasks.

On the other hand, if the application process has started (step S105: Yes), the list-up unit 104 starts judging whether the application process has been completed (step S106) to confirm the completion of the application process. If the application process has not been completed (step S106: No), the task classification process returns to step S102 and repeats the acquisition of task information during the execution of the application task.

When the application process is completed (step S106: Yes), the list-up unit 104 extracts related tasks in one application task from the temporary file 112 using the classification tag information and the process database 113 (step S107). Then, the list-up unit 104 outputs information on the extracted related tasks to the verification management unit 105.

The verification management unit 105 generates a confirmation screen that allows the user to select the tasks to be excluded and to select the display of the missing tasks. The verification management unit 105 then outputs the generated confirmation screen to the input/output processing unit 13, and causes the input/output device 12 to display it (step S108).

The verification management unit 105 determines whether the worker has selected the display of the omitted work (step S109). If the worker has not selected the display of the omitted work (step S109: No), the verification management unit 105 proceeds to step S111.

In contrast, if the missing task display is selected (step S109: Yes), the verification management unit 105 adds the specified missing task to the list of related tasks displayed on the confirmation screen (step S110).

Then, the verification management unit 105 acquires the information input by the worker using the input/output device 12 and checks whether it is correct (step S111). At this time, if there is a task to be excluded from the application task, the worker selects the task to be excluded and notifies the verification management unit 105. Also, if there is a missing task to be added as a related task, the worker selects the missing task to be added and notifies the verification management unit 105. After that, when the related tasks in the application task are confirmed, the worker presses the registration button. When the registration button is pressed, the verification management unit 105 judges the excluded task to be an error and the added missing task and the remaining tasks to be correct, checks whether they are correct, confirms them as related tasks of the application task, and outputs information on the confirmed related tasks to the grouping unit 106.

The grouping unit 106 receives input of information on related tasks from the verification management unit 105. The grouping unit 106 then compiles the related tasks for one application task and stores them in the task classification database 114 (step S112).

As described above, the work information management server according to this embodiment provides the worker with selectable information on missing tasks that were not extracted as related tasks for each specific application task, and includes the missing tasks selected by the worker in the related tasks. The work information management server then generates and stores a database in which related tasks are lumped together and classified. This allows the work information management server to more accurately classify related tasks for specific application tasks. Therefore, bottleneck analysis of application tasks can be performed more accurately, making it possible to improve work efficiency.

Figure 16 is a block diagram of a work information management server according to Example 4. The work information management server according to this example differs from Example 1 in that it is capable of detecting a frequently used window used in a specific application task and automatically opening the frequently used window when the specific application task is started. The work information management server 1 according to this example has a display candidate management unit 108 in addition to the units exemplified in Example 1. In the following explanation, the operation of each unit similar to that of Example 1 will be omitted.

Now, referring to FIG. 17, the flow of management of the task classification database using the frequency of use by the task information management server 1 according to this embodiment will be described. FIG. 17 is a flowchart of management of the task classification database using the frequency of use by the task information management server according to Example 4.

The display candidate management unit 108 monitors the processes executed by the process execution unit 22 and the windows displayed by the display control unit 21, and determines whether each application task stored in the task classification database 114 is being executed. Then, when there is an application task being executed that is the same as an application task stored in the task classification database 114, the display candidate management unit 108 identifies the window that was used during the execution of that application task (step S201).

Next, the display candidate management unit 108 counts and accumulates the number of times each task is performed using each window for each application task. After that, the display candidate management unit 108 determines the frequency of use of each window for each application task, and sorts the tasks for each application task stored in the task classification database 114 in descending order of frequency of use (step S202).

Then, the display candidate management unit 108 stores the related tasks sorted by application task together with information on the frequency of use of each task in the task classification database 114 (step S203).

In this embodiment, the frequency of use is calculated using the window used during the execution of the application task, but it is also possible to take into account the frequency of use of windows used before and after the execution of the application task. With reference to Figure 18, the flow of managing the task classification database using the frequency of use in this case will be described. Figure 18 is a flowchart of another example of managing the task classification database using the frequency of use.

The display candidate management unit 108 monitors the processes executed by the process execution unit 22 and the windows displayed by the display control unit 21, and determines whether each application task stored in the task classification database 114 is being executed. Then, when there is an application task being executed that is the same as an application task stored in the task classification database 114, the display candidate management unit 108 identifies the window that was used during the execution of that application task (step S211).

Furthermore, the display candidate management unit 108 identifies windows that were used close to the start or end of the application process (step S212).

Next, the display candidate management unit 108 counts and accumulates the number of times each task is performed using each window for each application task. After that, the display candidate management unit 108 obtains the frequency of use of each window for each application task, and sorts the tasks for each application task stored in the task classification database 114 in descending order of frequency of use (step S213).

Then, the display candidate management unit 108 stores the related tasks sorted by application task together with information on the frequency of use of each task in the task classification database 114 (step S214).

Next, the flow of window display processing using the frequency of use in application work will be described with reference to FIG. 19. FIG. 19 is a flowchart of window display processing using the frequency of use in application work.

The display candidate management unit 108 monitors the process executed by the process execution unit 22 and the window displayed by the display control unit 21 to determine whether the application process has started (step S301). If the application process has not started (step S301: No), the display candidate management unit 108 waits until the application process starts.

On the other hand, if the application process has started (step S301: Yes), the display candidate management unit 108 determines whether input has started (step S302). If input has not started (step S302: No), the display candidate management unit 108 waits until input starts.

In contrast, when input has started (step S302: Yes), the display candidate management unit 108 causes the display control unit 21 to display a screen that allows the operator to select whether or not to display frequently used windows, and checks whether or not to display the frequently used windows. The display candidate management unit 108 then determines whether or not to display the frequently used windows in accordance with the operator's selection (step S303). If the frequently used windows are not to be displayed (step S303: No), the display candidate management unit 108 proceeds to step S306.

In contrast, when displaying frequently used windows (step S303: Yes), the display candidate management unit 108 identifies frequently used tasks among the tasks related to the ongoing application process and acquires them from the task classification database 114. Then, the display candidate management unit 108 sets the windows used in the identified tasks as candidates for frequently used windows, and causes the display control unit 21 to display information about these candidates (step S304).

When the worker selects a window to display from the candidates, the display candidate management unit 108 causes the display control unit 21 to display the window selected by the worker (step S305). The worker performs each task in the application process using the displayed frequently used window.

Then, the display candidate management unit 108 monitors the process executed by the process execution unit 22 and the window displayed by the display control unit 21 to determine whether the application process has been completed (step S306). If the application process has not been completed (step S306: No), the display candidate management unit 108 waits until the application process is completed.

In contrast, if the application process is completed (step S306: Yes), the display candidate management unit 108 ends the display process of frequently used windows.

As described above, the work information management server according to this embodiment assists the worker in his/her work by displaying frequently used windows when performing application work. This allows the worker to perform application work efficiently.

In the above embodiments, the application work performed on one worker terminal 2 has been described as an example, but as shown in FIG. 20, application work performed on multiple terminal devices 2A to 2C may be managed together. FIG. 20 is a system configuration diagram when multiple worker terminals are connected.

In this case, information on tasks related to the application process on each of the terminal devices 2A to 2C can be used for analysis. Furthermore, learning can be performed using information on tasks related to the application process on each of the terminal devices 2A to 2C, and tasks related to the application process can be consolidated into one.

Furthermore, the window to be opened at the start of the application process as described in the second and fourth embodiments for each of the terminal devices 2A to 2C may be determined using all information on tasks related to the application process for each of the terminal devices 2A to 2C.

(Hardware configuration)
21 is a hardware configuration diagram of the work information management server 1 according to each of the above-mentioned embodiments. The work information management server 1 according to the above-mentioned embodiments can be realized by the hardware shown in FIG.

For example, as shown in FIG. 21, the work information management server 1 has a CPU (Central Processing Unit) 91, a memory 92, a hard disk 93, a display 94, an input device 95, and a network interface 96. The CPU 91 is connected to each of the memory 92, the hard disk 93, the display 94, the input device 95, and the network interface 96 via a bus.

The network interface 96 is, for example, a communication interface between the work information management server 1 and the worker terminal 2. The CPU 91 communicates with each part of the work information management server 1 via the network interface 96.

The display 94 and the input device 95 realize the input/output device 12. The input device 95 is, for example, a keyboard or a mouse. By using the display 94 and the input device 95, it is possible to access the task classification database 114 and analyze the application work.

The hard disk 93 realizes the functions of the data storage unit 11 illustrated in Figures 1, 11, and 16. The hard disk 93 also stores various programs including programs that realize the functions of the task classification processing unit 10, the analysis unit 14, and the input/output processing unit 13 illustrated in Figures 1, 11, and 16.

The CPU 91 reads out various programs stored in the hard disk 93, expands them on the memory 92, and executes them. As a result, the CPU 91 and memory 92 realize the functions of the task classification processing unit 10, the analysis unit 14, and the input/output processing unit 13 illustrated in Figures 1, 11, and 16. As the functions of the task classification processing unit 10, the CPU 91 and memory 92 realize the functions of the task information collection unit 101, the text extraction unit 102, the tagging unit 103, the list-up unit 104, the verification management unit 105, and the grouping unit 106 illustrated in Figures 1, 11, and 16. In addition, the CPU 91 and memory 92 realize the functions of the window management unit 107 and the display candidate management unit 108 illustrated in Figures 11 and 16 as the functions of the task classification processing unit 10.

REFERENCE SIGNS LIST 1 Work information management server 2 Worker terminal 10 Work classification processing unit 11 Data storage unit 12 Input/output device 13 Input/output processing unit 14 Analysis unit 21 Display control unit 22 Processing execution unit 101 Work information collection unit 102 Text extraction unit 103 Tag assignment unit 104 Listing unit 105 Verification management unit 106 Grouping unit 107 Window management unit 108 Display candidate management unit 109 Update unit 111 Work information database
112 Temporary file 113 Process database 114 Work classification database

Claims (11)

assigning a classification tag representing a task corresponding to each of a plurality of tasks performed using each of a plurality of active windows based on keywords extracted from each of the plurality of active windows;
extracting a plurality of tasks for each task based on a start time and an end time of the task identified based on the task and the type of the classification tag;
An information processing program that causes a computer to execute a process of grouping and recording the extracted information on the plurality of tasks for each business. making a request for confirmation of whether or not the correspondence between each of the extracted tasks and the business is correct for each of the extracted tasks for each of the business;
2. The information processing program according to claim 1, further comprising: making a computer execute a process of correcting the grouping of the recorded information of the work based on a result of each of the correctness checks. Acquire in advance related work information representing the work to be performed for each of the business tasks;
3. The information processing program according to claim 1, further comprising: causing a computer to execute a process of performing the extraction based on the start time of the task, the end time of the task, the type of the classification tag, and the related work information. The information processing program according to any one of claims 1 to 3, characterized in that the program causes a computer to execute a process of assigning the classification tag based on correspondence information including information on each of the keywords and the classification tag corresponding to each of the keywords that is stored in advance. The information processing program according to claim 4, characterized in that the computer is caused to execute a process of adding new keywords in the grouped and recorded tasks and the classification tags corresponding to the new keywords to the correspondence relationship information stored in advance. determining a frequency of use of each of the windows in each of the business operations;
6. The information processing program according to claim 1, further comprising: causing a computer to execute a process of rearranging and recording the grouped tasks in descending order of frequency of use. performing the extraction using the work performed using a predetermined period window that is the sum of the window used from the start time to the end time to the window used a predetermined time before and after the start time and the end time;
Calculating the frequency of use for each of the predetermined time windows;
The information processing program according to claim 6, further comprising: causing a computer to execute a process of rearranging the tasks to be executed using each of the predetermined period windows. The information processing program according to any one of claims 1 to 7, characterized in that, when a specific task is performed, the computer is caused to execute a process of automatically opening the window used for each of the plurality of tasks corresponding to the specific task among the grouped and recorded tasks. The information processing program according to claim 2, characterized in that, in the request for correctness confirmation, a missing task other than the multiple tasks extracted as the tasks corresponding to each of the tasks can be selected, and when the missing task is selected, the computer is caused to execute a process of adding the missing task to the multiple tasks extracted for the task for which the missing task was selected. An information processing device,
assigning a classification tag representing a task corresponding to each of a plurality of tasks performed using each of a plurality of active windows based on keywords extracted from each of the plurality of active windows;
grouping the work for each task based on the start time and end time of the task identified based on the task and the type of the classification tag;
The grouped information of the work is recorded for each task.
2. An information processing method comprising : a tagging unit that assigns, to each of a plurality of tasks performed using each of a plurality of active windows based on a keyword extracted from each of the plurality of active windows, a classification tag that indicates a task corresponding to each of the tasks among a plurality of tasks;
a list-up unit that extracts the work for each of the tasks based on a start time and an end time of the task that are specified based on the task and the type of the classification tag;
a grouping unit that groups and records information on the plurality of tasks for each business extracted by the list-up unit.

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