JP2018147352A - Business analysis apparatus, and business analysis method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To grasp, effectively and in detail, kind of business carried out by a user and time required for the business.SOLUTION: A business analysis apparatus stores operation log information which is information relating to an operation history of a user doing business by operating an information processing apparatus and schedule information which is information relating to business schedule of the user. The apparatus estimates contents of the business carried out by the user for each of time slots based on at least any of the operation log information and the schedule information. Further, the apparatus estimates the contents of the user's business at a time slot in which the business contents are not estimated, based on at least any of the operation log information and the schedule information and based on any of the business contents at the time slot in which the user's business contents are estimated by the operation log information and the business contents at the time slot in which the user's business contents are already estimated by the schedule information.SELECTED DRAWING: Figure 3

Description

The present invention relates to a business analysis device and a business analysis method.

  In Patent Document 1, “the time according to the type of work is automatically totaled with high accuracy”, “the operation association unit associates reference or creation with the operation log acquired by the operation log acquisition unit. The business name identification unit identifies the business name of each operation log, and the business name maintenance / change unit maintains the business name associated with the creation and the business associated with the creation. If the business name of one name and the business name associated with a reference that is temporally adjacent to one business name are related, the business name associated with the reference is changed to one business name. Execute the process, and the business time totaling unit totals each business time using the business name processed by the business name maintenance / change unit, so that when the user is creating one file Even if you reference another file, you can reference another file. Aggregate of as being the creation time of the file. Has been described as ".

JP 2011-164936 A

  In recent years, there has been a demand for further improvement in the efficiency of office work for the purpose of providing efficient services and reducing labor costs. When improving office work, for example, the daily work of users (workers) such as office workers who perform operations such as office work by operating a personal computer (hereinafter referred to as a business PC) is grasped and analyzed in detail. It is important to.

  In Patent Document 1, business names are specified based on operation logs acquired mechanically, and business hours are totaled. However, in this document, the correspondence table of the file name and the type of work contents prepared in advance is used, and if the file name of the correspondence table does not exist in the operation log, the operation time is calculated by ignoring the operation log. For example, when file names can be freely assigned, there is a high possibility that operation logs that do not exist in the correspondence table will increase and the calculation time and actual state will deviate. In this document, the switching time of the active window is assumed, and it is assumed that one file is activated in a certain time zone. For this reason, for example, it is difficult to apply when a plurality of files are operated simultaneously in a multi-window.

  The present invention has been made in view of such a background, and provides a business analysis device and a business analysis method capable of efficiently and in detail understanding the type of business performed by the user and the time required for the business. The purpose is to do.

One of the present invention for achieving the above object is a business analysis device, which is operation log information that is information related to an operation history of the information processing device of a user who operates the information processing device and performs business. Based on at least one of the operation log information and the schedule information, a storage unit that stores schedule information that is information related to the user's work schedule, and estimates the work contents performed by the user for each time zone. A job content estimation unit that stores the user's job content based on the operation log information and at least one of the operation log information and the schedule information. The business content in the time zone in which the business content of the user has been estimated based on the business content and the schedule information Based on at least one of out to estimate the work contents of the user in the time zone business content it is not estimated.

  In addition, the subject which this application discloses, and its solution method are clarified by the column of the form for inventing, and drawing.

According to the present invention, it is possible to efficiently grasp in detail the type of work performed by the user and the time required for the work.

1 is a diagram illustrating a schematic configuration of an information processing system. It is an information processing apparatus shown as an example of hardware of a business PC or a business analysis apparatus. It is a processing block diagram explaining the various functions and various information in an information processing system. It is an example of operation log information. It is an example of schedule information. It is an example of an operation log analysis table. It is an example of a keyword / business content correspondence table. It is a figure explaining a mode that a keyword business content estimation part estimates business content. It is an example of an operation log analysis table. It is an example of a schedule analysis table. It is a figure explaining the 2nd estimation method. It is a figure explaining the 3rd estimation method. It is a figure explaining the 4th estimation method. It is an example of an information relevance pattern. It is a figure explaining the process of a keyword learning part. It is an example of a work time table. It is a figure explaining the process of a work time table production | generation part. It is a figure explaining the process of a work time table production | generation part. It is a figure explaining the process of a work time table production | generation part. It is a figure which shows an example of the work time table for every work content. It is an example of a working time graph. It is a flowchart explaining a main process. It is a flowchart explaining an operation log analysis table production | generation process. It is a flowchart explaining a keyword work content estimation process. It is a flowchart explaining a keyword learning process. It is a flowchart explaining the estimation process by a 1st estimation method. It is a flowchart explaining the estimation process by a 2nd estimation method. It is a flowchart explaining the estimation process by a 3rd estimation method. It is a flowchart explaining the estimation process by a 4th estimation method. It is a flowchart explaining a work time table | surface production | generation process.

  Hereinafter, embodiments will be described in detail with reference to the drawings.

FIG. 1 shows a schematic configuration of an information processing system 1 shown as an embodiment. The information processing system 1 includes one or more information processing apparatuses (personal computers, etc.) (hereinafter referred to as a business PC 20) used by a user (worker) such as an office worker for business, and a business via a communication network 5. And a business analysis apparatus 100 that is communicably connected to the PC 20. The communication network 5 is, for example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or the like laid in an organization to which a user belongs.

  The business analysis apparatus 100 includes history information (hereinafter referred to as operation log information) related to operations performed by the user on the business PC 20 from the business PC 20 via the communication network 5, and information related to the user's business schedule and business plan ( Hereinafter, it is referred to as schedule information), and analysis of work performed by the user (specification of the type of work performed by the user, acquisition of time the user engaged in the work, etc.) is performed.

  FIG. 2 shows an information processing apparatus (computer) (hereinafter referred to as an information processing apparatus 10) shown as an example of hardware of the business PC 20 and the business analysis apparatus 100. The business PC 20 and the business analysis device 100 may be realized by using virtual resources such as a virtual server or a cloud server in a cloud system. The business PC 20 and the business analysis device 100 may be realized by, for example, a plurality of information processing devices and processors that are communicably connected.

  As illustrated in FIG. 1, the information processing apparatus 10 includes a processor 11, a main storage device 12, an auxiliary storage device 13, an input device 14, an output device 15, and a communication device 16. These are communicably connected to each other via a communication means such as a bus (not shown).

  The processor 11 is configured using, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). Various functions of the business PC 20 and the business analysis device 100 are realized by the processor 11 reading and executing the program stored in the main storage device 12. The main storage device 12 is a device that stores programs and data, and is, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a nonvolatile semiconductor memory (NVRAM (Non Volatile RAM)), or the like.

The auxiliary storage device 13 is, for example, a hard disk drive, SSD (Solid State Drive)
), Optical storage devices (CD (Compact Disc), DVD (Digital Versatile Disc), etc.), storage systems, IC cards, SD memory cards, recording media reading / writing devices such as optical recording media, and cloud server A storage area or the like. Programs and data stored in the auxiliary storage device 13 are loaded into the main storage device 12 as needed. For example, the auxiliary storage device 13 may be connected via a communication unit such as a network storage.

  The input device 14 is a user interface that receives external input, and is, for example, a keyboard, a mouse, a touch panel, or the like. The output device 15 is a user interface that provides various information such as processing progress and processing results, and is, for example, a screen display device (LCD (Liquid Crystal Display), graphic card, etc.), a printing device, or the like. For example, a configuration in which information is input to or output from another device via the communication device 16, that is, a configuration in which the communication device 16 functions as the input device 14 or the output device 15 may be employed.

  The communication device 16 is a wired or wireless communication interface that realizes communication with other devices performed via the communication network 5, and is, for example, a NIC (Network Interface Card) or a wireless communication module. .

FIG. 3 is a processing block diagram for explaining various functions and various information (data) in the information processing system 1. In the figure, only one business PC 20 is shown, but business PC 2
0 may be plural.

Each function shown in the figure is realized, for example, when the processor 11 of the information processing apparatus 10 reads and executes a program stored in the main storage device 12 or the auxiliary storage device 13. Further, the functions shown in the figure are realized by, for example, hardware (ASIC (Application Specific Integrated Circuit) or the like) included in the business PC 20 or the business analysis apparatus 100. The business PC 20 and the business analysis apparatus 100 may further include functions such as an operating system, a device driver, and a DBMS (DataBase Management System).

  As shown in the figure, the business PC 20 includes an information acquisition unit 211. Further, the business PC 20 stores each information of the operation log information 251 and the schedule information 252. The operation log information 251 is information generated by an operating system or application software operating on the business PC 20 and includes, for example, information on an operation history performed on the business PC 20 by the user. The schedule information 252 is information managed by application software (schedule management support software or the like) used by the user on the business PC 20, for example. The information acquisition unit 211 transmits the operation log information 251 and the schedule information 252 to the work analysis apparatus 100 as needed (for example, every time a preset time interval arrives) via the communication network 5.

  As shown in FIG. 3, the task analysis apparatus 100 includes an information collection unit 111, an operation log analysis table generation unit 112, a keyword task content estimation unit 113, an information setting unit 114, a task content estimation unit 115 based on information relevance, keyword learning. Unit 116, work time table generation unit 117, work content work time calculation unit 118, and work time graph display unit 119.

  As shown in the figure, the work analysis apparatus 100 includes an operation log information 151, a schedule information 152, an operation log analysis table 153, a schedule analysis table 154, a keyword / work content correspondence table 155, an information relevance pattern 156, a work time. A table 157 and a work time table 158 for each business content are stored. The business analysis apparatus 100 manages these pieces of information (data) using, for example, a file system or a DBMS.

  Among the above functions, the information collection unit 111 receives the operation log information 251 and the schedule information 252 sent from the business PC 20, receives the received operation log information 251 as the operation log information 151, and receives the received schedule information 252. Each is stored as schedule information 152.

  FIG. 4 shows an example of the operation log information 151. As shown in the figure, the operation log information 151 includes one or more records having items of a user ID 1511, a process ID 1512, a data name 1513, a data content 1514, an operation content 1515, and a date / time 1516. One record of the operation log information 151 corresponds to one piece of history information (hereinafter referred to as an operation log) generated by the business PC 20 in accordance with an operation performed by the user.

  Among the items described above, the user ID 1511 is set with information (hereinafter referred to as a user ID) that identifies the user of the business PC 20 who has performed the operation that triggered the generation of the operation log.

  The process ID 1512 is set with information (hereinafter referred to as a process ID) that identifies a process that has received an operation that triggered the generation of the operation log (or that has performed processing according to the operation).

The data name 1513 is set with information (hereinafter referred to as a data name) that identifies data that is an access target (operation target) that triggered the generation of the operation log. In this example, the data to be accessed is a file. In the data name 1513, the file name of the file to be accessed is set as the data name. Note that the data to be accessed (operation target) may be application software, Web content, application software applied by a cloud server, or the like in addition to a file. In this case, the data name 1513 includes, for example, application software The name (identifier) and URL (Uniform Resource Locator) of the program realizing the above are set.

  In the data content 1514, the substance of data specified by the data name 1513 (hereinafter referred to as data content) is set. In this example, text data included in the data specified by the data name 1513 is set in the data content 1514 as the entity.

In the operation content 1515, information indicating the content of the operation that triggered the generation of the operation log (hereinafter referred to as operation content) is set. In this example, the operation content 1515 includes “Open” indicating that an operation for opening a file has been performed, “Close” indicating that an operation for closing a file has been performed, and indicating that a file has been newly created. A character string such as “Create” and “Change” indicating that the content of the file has been changed (for example, the file size or the hash value of the file has changed) is set as the operation content.

  In the date and time 1516, information indicating the date and time when the log information is generated is set.

  FIG. 5 shows an example of the schedule information 152. As shown in the figure, the schedule information 152 is composed of one or more records having items of a user ID 1521, a schedule name 1522, a start date and time 1523, and an end date and time 1524. One record of the schedule information 152 corresponds to one schedule scheduled (planned) by the user for the work.

  A user ID is set as the user ID 1521. In the schedule name 1522, information for specifying the contents of the schedule (hereinafter referred to as schedule name) is set. The start date / time 1523 is set to the scheduled start date / time of the schedule, and the end date / time 1524 is set to the scheduled end date / time of the schedule.

  Returning to FIG. 3, the operation log analysis table generation unit 112 generates the operation log analysis table 153 based on the information of the operation log information 151. Specifically, the operation log analysis table generation unit 112 aggregates a plurality of records having the same user ID 1511, process ID 1512, and data name 1513 in the operation log information 151 into one record, thereby generating the operation log analysis table 153. Generate.

  FIG. 6 shows an example of the operation log analysis table 153. As shown in the figure, the operation log analysis table 153 includes items of user ID 1531, process ID 1532, data name 1533, data content 1534, start date and time 1535, end date and time 1536, operation / update date and time 1537, and business content 1538. It consists of one or more records. One record of the operation log analysis table 153 includes information regarding a series of operations performed on specific data.

A user ID is set as the user ID 1531. A process ID is set in the process ID 1532. A data name is set in the data name 1533. In the data content 1534, the data content is set. In the start date and time 1535, the date and time when the operation on the data is started (for example, the date and time when the file that is the data is opened) is set. In the end date and time 1536, the date and time when the operation on the data is completed (for example, the date and time when the file that is the data is closed) is set. The operation / update date / time 1537 is set with the date / time when the operation (excluding operations corresponding to the start date / time 1535 and the end date / time 1536) is performed (for example, the date and time when the content of the file as the data is changed). Is done.

  In the business content 1538, information indicating the content of business performed by the user (hereinafter referred to as business content) estimated by the keyword business content estimation unit 113 for each record is set. FIG. 6 shows a state before the business content is estimated.

  Returning to FIG. 3, the keyword task content estimation unit 113 performs the operation based on the operation log analysis table 153 (the content other than the task content 1538) generated by the operation log analysis table generation unit 112 and the keyword / work content correspondence table 155. The business content is estimated for each record in the log analysis table 153, and information indicating the estimated business content is set in the business content 1538. Further, the keyword job content estimation unit 113 estimates the job content for each record of the schedule information 152 based on the schedule information 152 and the keyword / work content correspondence table 155, and sets the schedule information 152 and the estimated job content. A schedule analysis table 154 is generated.

  FIG. 7 shows an example of the keyword / business content correspondence table 155. As shown in the figure, the keyword / business content correspondence table 155 manages the correspondence between the keywords 1551 and the business content 1552. The contents of the keyword / business content correspondence table 155 are set by the user via the information setting unit 114, for example.

  FIG. 8 is a diagram for explaining how the keyword task content estimation unit 113 estimates task content. The keyword task content estimation unit 113 determines, for each record in the operation log analysis table 153, whether or not the keyword 1551 of the keyword / task content correspondence table 155 is included in the data name 1533 of the operation log analysis table 153. If 1551 is included, the business content 1552 associated with the keyword 1551 is estimated as the business content of each record. In addition, for each record of the schedule information 152, the keyword task content estimation unit 113 determines whether or not the keyword 1551 of the keyword / task content correspondence table 155 is included in the schedule name 1522, and the keyword 1551 is included. The business content 1552 associated with the keyword 1551 is estimated as the business content of each record.

  FIG. 9 shows an example of the operation log analysis table 153 in which the business content estimated by the keyword business content estimation unit 113 is set. As shown in the figure, the estimated business content is set in the business content 1538 of the operation log analysis table 153. The operation log analysis table 153 includes records for which the business content is not estimated. “(Not set)” is set in the business content 1538 of the record whose business content is not estimated.

  FIG. 10 shows an example of the schedule analysis table 154 generated by the keyword task content estimation unit 113 based on the schedule information 152 and the estimated task details. As shown in the figure, the estimated business content is set in the business content 1545 of the schedule analysis table 154. Note that the schedule analysis table 154 includes records for which the business content of the schedule information 152 is not estimated. “(Not set)” is set in the business content 1545 of the record whose business content is not estimated.

  Returning to FIG. 3, the business content estimation unit 115 based on information relevance (hereinafter referred to as the business content estimation unit 115) could not estimate the business content by keyword search of the keyword business content estimation unit 113. For the record of the operation log analysis table 153 or the schedule information 152, the business content is estimated by another method.

  For example, for the record (hereinafter, referred to as “unset record”) in which the operation content 1538 of the operation log analysis table 153 is not set, the job content estimation unit 115 sets the data content 1534 (file content, electronic The data name 1533 (file name, etc.) of another record (hereinafter referred to as a set record) in which the business content 1538 is set is included in the content of the mail text, the file name of the attached file, etc. In this case, the business content 1538 of the set record is estimated as the business content 1538 of the unset record. Hereinafter, this method is referred to as a “first estimation method”.

  In addition, for example, the business content estimation unit 115 includes a temporal relationship between records in the operation log analysis table 153 and a record in the schedule analysis table 154 (hereinafter referred to as a continuous time condition), a time interval before and after (hereinafter referred to as a continuous time condition) For example, the operation log analysis table 153 or the schedule for the record in which the operation content of the operation log analysis table 153 or the schedule analysis table 154 is not set (hereinafter referred to as an unset record). The business content 1545 of the record in which the business content of the analysis table 154 has been set (hereinafter referred to as a set record) is estimated as the business content of the unset record. Hereinafter, this method is referred to as a “second estimation method”.

  FIG. 11 is a diagram for explaining the second estimation method. In the example shown in the figure, the non-set record (record about the log information of the file “A.doc” in the operation log analysis table 153) is temporally continuous (following a predetermined time interval or less), This is a case where there is a set record in the schedule analysis table 154 (a record in which the business content “main business” is set). In this case, the business content estimation unit 115 estimates “main business” which is the business content of the set record 1545 of the schedule analysis table 154 as the business content 1538 of the unset record of the operation log analysis table 153.

  Further, for example, the business content estimation unit 115 records from the operation log analysis table 153 that the business content 1538 is not set (hereinafter, referred to as an unset record) and the start date and time 1535 to the end date and time 1536 of the unset record. For other records in which the business contents 1538 have been set (hereinafter referred to as “set records”), which are overlapped with the time zone, are not set based on the status of access to the data to be accessed. Estimate the work contents of the record. Hereinafter, the business content estimation process based on this method is referred to as a “third estimation method”.

  FIG. 12 is a diagram for explaining the third estimation method. In this example, the file “B.xls” is the access target for the unset record, and the file “A.ppt” is the access target for the set record. In this case, the business content estimation unit 115 overlaps the open time of the non-set record and the set record, and “A.ppt” and “B.xls” are alternately updated during the overlapped time zone. The two files are accessed in the same job because the alternate update time interval is shorter than a preset time interval (for example, 10 minutes, hereinafter referred to as update information time interval). It is presumed that the job contents set in the set record are “general affairs” as the job contents of the unset record.

  Further, for example, the business content estimation unit 115 includes a record in which the business content 1538 of the operation log analysis table 153 is not set (hereinafter referred to as an unset record) and another record in which the business content 1538 is set (hereinafter referred to as “non-set record”). , Referred to as a set record)) based on the commonality (identity, similarity (similarity)) of the location of the data to be accessed (for example, the folder in which the file is stored). Estimate the business contents of the setting record. Hereinafter, the business content estimation process based on this method is referred to as a “fourth estimation method”.

  FIG. 13 is a diagram (folder structure diagram) for explaining the fourth estimation method. For example, when a file to be accessed for an unset record is stored in “folder 1-1” and a file to be accessed for a set record is also stored in the same “folder 1-1”, the business content estimation unit 115 estimates the business content of the set record as the business content of the unset record. On the other hand, even if there is no file to be accessed for the set record in the same folder as the file to be accessed for the unset record, for example, a parent set in advance from the folder in which the file to be accessed for the unset record is stored When the file to be accessed for the set record is stored in a folder within the number of files (hereinafter referred to as the “threshold relative number”), the job content estimation unit 115 sets the job content set for the set record. Is estimated as the business content of the unset record. For example, in the same figure, when the file to be accessed of the unset record is stored in “Folder 2-1” and the threshold closeness is set to “1”, it has been set to “Folder 1-1”. If the file to be accessed is stored, the business content of the set record is estimated as the business content of the unset record.

  According to at least one of the first to fourth estimation methods described above, the operation log analysis table 153 or the schedule information 152 record in which the business content could not be estimated by the keyword search of the keyword business content estimation unit 113 The business content can be estimated efficiently and accurately.

  Returning to FIG. 3, the task analysis apparatus 100 stores parameters such as a continuous time condition, a continuous time interval, an update information time interval, and a threshold relative degree used in each estimation process described above as an information relevance pattern 156. . The content of the information relevance pattern 156 is preset by the user via a user interface provided by the information setting unit 114, for example.

  FIG. 14 shows an example of the information relevance pattern 156. The information relevance pattern 156 shown in the figure is composed of one or more records having items of a parameter name 1561 and a set value 1562. In the parameter name 1561, the name of a parameter (continuous time condition, continuous time interval, update information time interval, threshold degree equality) is set. In the setting value 1562, the contents (values) of each parameter are set.

  Returning to FIG. 3, the keyword learning unit 116 newly generates (learns) the correspondence between the keyword and the business content based on the operation log analysis table 153 or the schedule analysis table 154, and displays the generated content as a keyword / business content correspondence table. To 155.

  FIG. 15 is a diagram for explaining the processing performed by the keyword learning unit 116, and describes how the keyword learning unit 116 newly generates a correspondence between the keyword and the business content and outputs it to the keyword / business content correspondence table 155. FIG.

As shown in the figure, the keyword learning unit 116 has a common word (word, word) included in each data content 1534 of a plurality of records having the same (common) business content 1538 in the operation log analysis table 153. Idioms, phrases, sentences, etc.), the extracted words are used as keywords 1551, and the business contents 1538 set in common in each record are used as business contents 1552, and these are associated with each other in the keyword / business contents correspondence table 155. to add. It should be noted that the keyword learning unit 116 has a common word (word) included in each schedule name 1542 (may be a schedule entity) of a plurality of records having the same (common) business content 1545 in the schedule analysis table 154. , Idioms, phrases, sentences, etc.), the extracted words are used as keywords 1551, and business contents 1538 set in common in each record are used as business contents 1552. You may make it add to.

  Returning to FIG. 3, the work time table generation unit 117 generates a work time table 157 based on the operation log analysis table 153 and the schedule analysis table 154.

  FIG. 16 shows an example of the work time table 157. The work time table 157 is acquired from each record of the schedule analysis table 154, which is obtained from each record of the operation log analysis table 153, and which associates the user ID 1531, the business content 1538, the start date and time 1535, and the end date and time 1536. And a record in which the user ID 1541, the business content 1545, the start date and time 1543, and the end date and time 1544 are associated with each other.

  Note that when the work time table generation unit 117 generates the work time table 157, the time zone (start date / time 1535 and end date / time 1536) between different records (records of the operation log analysis table 153 or records of the schedule analysis table 154). The specified time zone or the time zone specified by the start date and time 1543 and the end date and time 1544 may overlap. In this case, the work time table generation unit 117 generates the work time table 157 by specifying the work contents in the overlapping time zone as follows, for example.

  For example, as shown in FIG. 17, when the time zone overlaps between the record of the operation log analysis table 153 and the record of the schedule analysis table 154, the work contents of each record in the overlapped time zone are the same. The time table generating unit 117 generates the work time table 157 by adopting the earlier start date and time and the later end date and time.

  Also, for example, as shown in FIG. 18, when the time zones overlap between the plurality of records of the operation log analysis table 153, and the business contents of the records in the overlapping time zones are different, the work time table generation unit 117 Generates the work time table 157 by adopting the business contents of the record that is updated with respect to the data (for example, file) that is the access target of each record. In this case, for example, the work time table generation unit 117 acquires information related to data update (change in file size, change in hash value obtained for a file, etc.) from the operation log information 151, and the acquired information is included in the acquired information. Based on this, it is determined whether or not data is updated in each time zone.

  For example, as shown in FIG. 19, the time zone overlaps between the record of the operation log analysis table 153 and the record of the schedule analysis table 154, the business contents in the overlapping time zone are different, and the operation When the data (for example, a file) to be accessed is not updated in the record of the log analysis table 153, the work time table generation unit 117 preferentially adopts the business contents of the record of the schedule analysis table 154. The work time table 157 is generated.

  Returning to FIG. 3, the work content by work content calculation unit 118 is based on the work time table 157, specifically, the work content for each user based on the time width of each time zone and the business content of each time zone. The work time for each work content 158 is generated by accumulating the work time for each work.

  FIG. 20 shows an example of the work content work time table 158 generated by the work content work time calculation unit 118. As shown in the figure, the work content work time table 158 includes information indicating the total time 1583 for each work content 1582 performed by each user (user ID 1581).

Returning to FIG. 3, the work time graph display unit 119 provides the user with information based on the work content work time table 158. For example, the work time graph display unit 119 outputs a screen (hereinafter, referred to as a work time graph 2100) showing the contents of the work time table 158 for each work content from the output device 15. FIG. 21 shows an example of the work time graph 2100.

  Next, processing performed by the task analysis apparatus 100 will be described.

  FIG. 22 is a flowchart (hereinafter referred to as main process S2200) for explaining the main flow of the process performed by the task analysis apparatus 100. Assuming that the main process S2200 is performed, it is assumed that the information collection unit 111 of the business analysis apparatus 100 has acquired the operation log information 151 and the schedule information 152 for a certain period from one or more business PCs 20. The main process S2200 is started, for example, when an execution instruction is received from a user or when a scheduled time has arrived. The contents of the latest keyword / business content correspondence table 155 are used at the time of execution of the main processing S2200 each time.

  As shown in the figure, first, the operation log analysis table generation unit 112 of the job analysis apparatus 100 generates an operation log analysis table 153 based on the operation log information 151 (hereinafter referred to as operation log analysis table generation processing S2210). )I do.

  FIG. 23 is a flowchart for explaining the details of the operation log analysis table generation processing S2210. Hereinafter, the operation log analysis table generation processing S2210 will be described with reference to FIG.

  As shown in the figure, the operation log analysis table generation unit 112 first extracts a record having a common user ID, process ID, and data name from the operation log information 151 (S2211).

  Subsequently, the operation log analysis table generation unit 112 aggregates the extracted records and outputs them to the operation log analysis table 153 (S2212).

  Subsequently, the operation log analysis table generation unit 112 outputs records other than the above-described record extracted from the operation log information 151 in S2211 to the operation log analysis table 153 (S2213).

  Returning to FIG. 22, the keyword work content estimation unit 113 of the work analysis apparatus 100 then estimates the work content of each record in the operation log analysis table 153 based on the keyword / work content correspondence table 155 and schedule information 152. The process contents of each record are estimated and a schedule analysis table is generated. Hereinafter, this process is referred to as keyword job content estimation process S2220.

  FIG. 24 is a flowchart for explaining the details of the keyword task content estimation process S2220. The keyword job content estimation process S2220 will be described below with reference to FIG.

  As shown in the figure, first, the keyword task content estimation unit 113 selects one record for which task details are not set (hereinafter referred to as an unset record) from the operation log analysis table 153 (S2221).

  Subsequently, the keyword task detail estimation unit 113 determines whether or not the keyword 1551 of the keyword / task detail correspondence table 155 is included in the data name 1533 of the selected unset record (S2222). If the keyword 1551 is included (S2222: YES), the process proceeds to S2223. If the keyword 1551 is not included (S2222: NO), the process proceeds to S2224.

In step S <b> 2223, the keyword job content estimation unit 113 acquires the job content 1552 associated with the keyword 1551 included in the data name 1533 from the keyword / work content correspondence table 155, and stores the acquired job content 1552 in the operation log. Set in an unset record in the analysis table 153.

  In step S <b> 2224, the keyword task content estimation unit 113 determines whether all the unset records in the operation log analysis table 153 have been selected. If all the unset records have not been selected (S2224: NO), the process returns to S2221. If all the unset records have been selected (S2224: YES), the process proceeds to S2225.

  In S <b> 2225, the keyword task content estimation unit 113 selects one record whose task details have not been estimated (hereinafter referred to as “unestimated record”) from the schedule information 152.

  Subsequently, the keyword task detail estimation unit 113 determines whether or not the keyword 1551 of the keyword / task detail correspondence table 155 is included in the schedule name 1522 of the selected non-estimated record (S2226). If the keyword 1551 is included (S2226: YES), the process proceeds to S2227. If the keyword 1551 is not included (S2226: NO), the process proceeds to S2228.

  In S <b> 2227, the keyword task content estimation unit 113 acquires the task content 1552 associated with the keyword 1551 included in the data name 1533 from the keyword / task content correspondence table 155, and acquires the content of the unestimated record. A record in which the business content 1552 is set is output to the schedule analysis table 154.

  In S2228, the keyword task content estimation unit 113 determines whether all the unestimated records in the schedule information 152 have been selected. If all the unestimated records have not been selected (S2228: NO), the process returns to S2225. If all the unestimated records have been selected (S2228: YES), the process proceeds to S2230 in FIG.

  Returning to FIG. 22, the keyword learning unit 116 of the task analysis device 100 newly generates a correspondence between the keyword and the task content based on the operation log analysis table 153 and the schedule analysis table 154, and the generated keyword and task A process of adding a combination of contents to the keyword / business contents correspondence table 155 (hereinafter referred to as keyword learning process S2230) is performed. The correspondence between the keyword newly generated (learned) by the keyword learning unit 116 and the business content is used for the estimation of the business content thereafter. For this reason, as the number of times the business analysis apparatus 100 is used increases, the estimation accuracy of the business content is also improved.

  FIG. 25 is a flowchart illustrating the details of the keyword learning process S2230. The keyword learning process S2230 will be described below with reference to FIG.

  As shown in the figure, first, the keyword learning unit 116 extracts a record group in which the same business content is set from the operation log analysis table 153 (S2231).

  Subsequently, the keyword learning unit 116 determines whether there is a common word in the data contents 1534 of each record of the extracted record group (S2232). If there is a common word (S2232: YES), the process proceeds to S2233. If there is no common word (S2232: NO), the process proceeds to S2234.

  In S2233, the keyword learning unit 116 adds a combination of a common word and a common business content to the keyword / business content correspondence table 155 (S2233).

In S <b> 2234, the keyword learning unit 116 determines whether or not all record groups having the same business content have been extracted from the operation log analysis table 153. If all record groups having the same business content have been extracted (S2234: YES), the process proceeds to S2240 in FIG. If not all records having the same business content have been extracted (S2234: NO), the process returns to S2231.

  Returning to FIG. 22, subsequently, the business content estimation unit 115 of the business analysis apparatus 100 records the business content 1545 of the operation log analysis table 153 and the schedule analysis table 154 (the business content in the keyword business content estimation processing S2220). Processing for estimating the business content by at least one of the first estimation method to the fourth estimation method described above (hereinafter referred to as business content estimation processing S2240 based on information relevance) To do so). Note that the first to fourth estimation methods do not necessarily have to implement all the methods. Moreover, you may implement combining 2 or more of these methods. The execution order in the case of performing a plurality of methods is not necessarily limited.

  FIG. 26 is an example of a task content estimation process S2240 based on information relevance, and an example of a process (hereinafter referred to as an estimation process S2600 based on the first estimation method) when task content is estimated by the first estimation method described above. It is a flowchart explaining these. Hereinafter, the estimation process S2600 according to the first estimation method will be described with reference to FIG.

  As shown in the figure, the business content estimation unit 115 first determines whether or not there is a record in which the business content 1538 is not set (hereinafter referred to as an unset record) in the operation log analysis table 153 (S2611). ). If there is a record in which the business content 1538 is not set (S2611: YES), the process proceeds to S2612. If there is no unset record (S2611: NO), the process proceeds to S2250 in FIG. 22, or at least one of the second to fourth estimation methods is executed.

  In S2612, the business content estimation unit 115 selects one unset record from the operation log analysis table 153.

  Subsequently, the business content estimation unit 115 stores the data name 1533 of the record (hereinafter referred to as a “set record”) in which the business content 1538 of the operation log analysis table 153 is set in the data content 1534 of the selected unset record. It is determined whether it is included (S2613). When the data name 1533 of the set record is included in the data content 1534 of the selected unset record (S2613: YES), the work content estimation unit 115 selects the work content set in the set record. It is set in the business content 1538 of the unset record in the middle (S2614). On the other hand, if the data name 1533 of the set record is not included in the data content 1534 of the selected unset record (S2613: NO), the process proceeds to S2615.

  In step S <b> 2615, the task content estimation unit 115 determines whether all unset records have been selected from the operation log analysis table 153. If all the unset records have not been selected (S2615: NO), the process returns to S2612. If all the unset records have been selected (S2615: YES), the process proceeds to S2250 in FIG. 22, or at least one of the second to fourth estimation methods is subsequently executed.

  FIG. 27 is an example of a task content estimation process S2240 based on information relevance, and an example of a process (hereinafter referred to as an estimation process S2700 based on the second estimation method) when task content is estimated by the second estimation method described above. It is a flowchart explaining these. Hereinafter, the estimation process S2700 based on the second estimation method will be described with reference to FIG.

As shown in the figure, the business content estimation unit 115 first determines whether or not there is a record in which the business content 1545 is not set in the operation log analysis table 153 or the schedule analysis table 154 (hereinafter referred to as an unset record). Is determined (S2711). If an unset record exists (S2711: YES), the process proceeds to S2712. If an unset record does not exist (S2711: NO), the process proceeds to S2250 in FIG. 22, or at least one of the first estimation method, the third estimation method, and the fourth estimation method is continuously executed. The

  In S2712, the business content estimation unit 115 acquires the continuous interval time and the continuous time condition from the information relevance pattern 156.

  Subsequently, the business content estimation unit 115 acquires a combination of records satisfying the acquired continuous interval time and continuous time condition from the operation log analysis table 153 and the schedule analysis table 154 (S2713). Note that one of the records acquired at this time is an unset record, and the other is a record for which business contents have been set (hereinafter referred to as a set record).

  Subsequently, the business content estimation unit 115 sets the business content set in one of the acquired combinations as the business content of the other record (S2714).

  Subsequently, the task content estimation unit 115 determines whether all unset records have been selected from the operation log analysis table 153 or the schedule analysis table 154 (S2715). If not all unset records have been selected (S2715: NO), the process returns to S2713. If all the unset records have been selected (S2715: YES), the process proceeds to S2250 in FIG. 22, or at least one of the first estimation method, the third estimation method, and the fourth estimation method continues. Is executed.

  FIG. 28 is an example of a task content estimation process S2240 based on information relevance, and an example of a process (hereinafter referred to as an estimation process S2800 by the third estimation method) when task content is estimated by the third estimation method described above. It is a flowchart explaining these. Hereinafter, the estimation process S2800 according to the third estimation method will be described with reference to FIG.

  As shown in the figure, the business content estimation unit 115 first determines whether or not there is a record in which the business content is not set (hereinafter referred to as an unset record) in the operation log analysis table 153 (S2811). . If an unset record exists (S2811: YES), the process proceeds to S2812. If there is no unset record (S2811: NO), the process proceeds to S2250 in FIG. 22, or the business content estimation unit 115 continues among the first estimation method, the second estimation method, and the fourth estimation method. At least one of the above is executed.

  In S <b> 2812, the business content estimation unit 115 acquires the update information interval time from the information relevance pattern 156.

  Subsequently, the task content estimation unit 115 acquires a combination of records satisfying the acquired update information interval time from the operation log analysis table 153 (S2813). Note that one of the records acquired at this time is an unset record, and the other is a record for which business contents have been set (hereinafter referred to as a set record).

  Subsequently, the business content estimation unit 115 sets the business content set for one of the acquired combinations as the business content of the other record (S2814).

Subsequently, the business content estimation unit 115 determines whether all unset records have been selected from the operation log analysis table 153 (S2815). If all the unset records have not been selected (S2815: NO), the process returns to S2812. If all the unset records have been selected (S2815: YES), the process proceeds to S2250 in FIG. 22, or at least one of the first estimation method, the second estimation method, and the fourth estimation method continues. Is executed.

  FIG. 29 is an example of a task content estimation process S2240 based on information relevance, and an example of a process when the task content is estimated by the above-described fourth estimation method (hereinafter referred to as an estimation process S2900 by the fourth estimation method). It is a flowchart explaining these. Hereinafter, the estimation process S2900 according to the fourth estimation method will be described with reference to FIG.

  As shown in the figure, the business content estimation unit 115 first determines whether or not a record in which the business content is not set (hereinafter referred to as an unset record) exists in the operation log analysis table 153 (S2911). . If an unset record exists (S2911: YES), the process proceeds to S2912. If there is no unset record (S2911: NO), the process proceeds to S2250 in FIG. 22, or at least one of the first to third estimation methods is continuously executed.

  In step S <b> 2912, the business content estimation unit 115 selects one unset record from the operation log analysis table 153.

  Subsequently, the business content estimation unit 115 acquires the threshold closeness number from the information relevance pattern 156 (S2913).

  Subsequently, the business content estimation unit 115 records the business content that has been set in a folder within the threshold parental degree from the folder in which the data specified by the data name 1533 of the unset record being selected is stored (hereinafter referred to as “record”). It is determined whether or not the data specified by the data name 1533 of the set record is stored (S2914). When such data is stored in a folder within the threshold degree of equality (S2914: YES), the business content of the set record is set to the business content 1538 of the unset record being selected (S2915). On the other hand, if such data is not stored in a folder within the threshold degree of equality (S2915: NO), the process proceeds to S2916.

  Subsequently, the business content estimation unit 115 determines whether all unset records have been selected from the operation log analysis table 153 (S2916). If all the unset records have not been selected (S2915: NO), the process returns to S2912. If all the unset records have been selected (S2915: YES), the process proceeds to S2250 in FIG. 22, or at least one of the first to third estimation methods is executed.

  Returning to FIG. 22, the work time table generation unit 117 of the work analysis apparatus 100 generates a work time table 157 based on the operation log analysis table 153 and the schedule analysis table 154 (hereinafter, work time table generation process S2250). Is called).

  FIG. 30 is a flowchart for explaining the details of the work time table generation processing S2250. Hereinafter, the work time table generation processing S2250 will be described with reference to FIG.

  As shown in the figure, the work time table generating unit 117 first extracts records that do not overlap with other records from the operation log analysis table 153 and the schedule analysis table 154, and extracts the extracted records as work time. It outputs to a table | surface (S3011).

Subsequently, the work time table generation unit 117 determines whether or not there is a record that overlaps with other records in the operation log analysis table 153 and the schedule analysis table 154 (S3012). When there is a record that overlaps with other records in time zone (S3012: YES)
), The process proceeds to S3013. If there is no record that overlaps with other records (S3012: NO), the process proceeds to S2260 in FIG.

  In step S3013, the work time table generation unit 117 selects one combination of records having overlapping time zones.

  In step S3014, the work time table generation unit 117 determines the type of the selected combination. If any record of the selected combination is a record in the operation log analysis table 153 (S3014: operation log analysis table), the process proceeds to S3015. On the other hand, when one of the selected combinations is a record in the operation log analysis table 153 and the other is a record in the schedule analysis table 154 (S3014: different type), the process proceeds to S3018.

  In S3015, the work time table generation unit 117 determines whether or not the business content of each record of the selected combination is the same. If they are the same (S3015: YES), the process proceeds to S3016, and if they are different (S3015: NO), the process proceeds to S3017.

  In S3016, the work time table generation unit 117 selects the earlier of the two records for the start time, selects the later of the two records for the end time, and operates the record in which the selected content is set. Output to the timetable. Thereafter, the process proceeds to S3021.

  In step S <b> 3017, the work time table generation unit 117 selects the business content of the record being updated from the two records of the selected combination, and outputs the record in which the selected business content is set to the work time table. Thereafter, the process proceeds to S3021.

  In S3018, the work time table generation unit 117 determines whether or not the business content of each record of the selected combination is the same. If they are the same (S3018: YES), the process proceeds to S3019, and if they are different (S3018: NO), the process proceeds to S3020.

  In S3019, the earlier of the two records is selected for the start time, the later of the two records is selected for the end time, and the record in which the selected content is set is output to the work time table. Thereafter, the process proceeds to S3021.

  In S3020, if the operation is performed on the data in the overlapping time zone, the operation content of the operation log analysis table 153 is selected, and if the operation is not performed, the operation content of the schedule analysis table 154 is selected. Output to work time table. Thereafter, the process proceeds to S3021.

  In step S3021, the work time table generation unit 117 determines whether all combinations of records having overlapping time zones have been selected. If not all combinations of records with overlapping time zones have been selected (S3021: NO), the process returns to S3013. If all combinations of records with overlapping time zones have been selected (S3021: YES), the process proceeds to S2260 in FIG.

  Returning to FIG. 22, subsequently, the work content work time calculation unit 118 of the work analysis apparatus 100 generates a work content work time table 158 based on the work time table 157.

  Subsequently, the work time graph display unit 119 of the work analysis apparatus 100 generates and outputs a work time graph 2100 based on the work content work time table 158.

As described above in detail, according to the task analysis apparatus 100 of this embodiment, the operation log information 151 and the schedule information 152 are used to efficiently calculate the type of task performed by the user and the time required for the task. It can be understood in detail well. Further, the task analysis apparatus 100 can accurately determine the type of task performed by the user and the time required for the task even when a file name can be freely assigned or when a plurality of files are operated simultaneously in multiple windows. I can grasp it.

  Needless to say, the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the invention. For example, the above embodiment has been described in detail for easy understanding of the present invention, and is not necessarily limited to the one having all the configurations described. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of the above embodiment.

Each of the above-described configurations, function units, processing units, processing means, and the like may be realized in hardware by designing some or all of them, for example, with an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files for realizing each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

  Further, in each of the above drawings, control lines and information lines indicate what is considered necessary for explanation, and not all control lines and information lines on the mounting are necessarily shown. For example, it may be considered that almost all configurations are actually connected to each other.

  Moreover, the arrangement | positioning form of the various function parts of the business analysis apparatus 100 demonstrated above, various process parts, and various databases is only an example. The arrangement form of the various function units, the various processing units, and the various databases can be changed to an optimum arrangement form from the viewpoint of the performance of hardware and software provided in the business analysis apparatus 100, processing efficiency, communication efficiency, and the like.

  The database configuration (schema) described above can be flexibly changed from the viewpoints of efficient use of resources, improvement of processing efficiency, improvement of access efficiency, improvement of search efficiency, and the like.

1 Information processing system, 5 communication network, 20 business PC, 100 business analysis device, 111 information collection unit, 112 operation log analysis table generation unit, 113 keyword business content estimation unit, 114 information setting unit, 115 information related pattern business content estimation , 116 Keyword learning unit, 117 Work time table generation unit, 118 Work time per work content calculation unit, 119 Work time graph display unit, 151 Operation log information, 152 Schedule information, 153 Operation log analysis table, 154 Schedule analysis table, 155 Keyword / work content correspondence table, 156 information relevance pattern, 157 work time table, 158 work time per work content, S2000 main process, S2210 operation log analysis table generation process, S2220 keyword work content estimation process, S2230 keyword learning process , S2600 estimation processing according to the first estimating method, the estimation processing by the S2700 second estimation method, S2800 estimation processing according to the third estimation method, S2900 estimation processing according to the fourth estimating method, S2250 work time table generating process

Claims (15)

A storage unit that stores operation log information that is information related to an operation history of the information processing device of a user who operates the information processing device and schedule information that is information related to the user's business schedule;
Based on at least one of the operation log information and the schedule information, a business content estimation unit that estimates and stores business content performed by the user for each time zone;
With
The business content estimation unit is configured to determine the user's business content in the time zone in which the business content of the user has been estimated based on at least one of the operation log information and the schedule information and the operation log information. Based on at least one of the business contents in the time zone in which the business content has been estimated, the business content of the user in the time zone in which the business content is not estimated,
Business analysis device. The business analysis apparatus according to claim 1,
The business content estimation unit
From the operation log information, first information that is information related to data accessed by the user in a first time zone in which the user's business content has not been estimated, and a second time in which the user's business content has been estimated. Obtaining second information, which is information relating to data that the user was accessing to the belt,
When the second information is included in the first information, the business content in the second time zone in which the business content of the user has been estimated is represented by the first time zone in which the business content is not estimated. Estimate as user's work content,
Business analysis device. The business analysis apparatus according to claim 1,
The business content estimation unit is within a time range set in advance from a first time zone in which the user's business content is not estimated and the operation log information grasps that the user has accessed data. When there is a second time zone in which the work content of the user has been estimated by the schedule information, the work content in the second time zone is changed to the user's work time in the first time zone in which the work content is not estimated. Estimate as business content,
Business analysis device. The business analysis apparatus according to claim 1,
The business content estimation unit includes a first time period in which the user's business content is not estimated, the first time zone in which the user has accessed the first data from the operation log information, and the user's business content Is overlapped with a second time zone in which it is determined from the operation log information that the user has accessed the second data, and a preset time is set in the overlapping time zone. When the user alternately accesses the first data and the second data within the interval, the business content in the second time zone in which the business content has been estimated is the first business data whose business content has not been estimated. Estimating the user's work contents in one hour,
Business analysis device. The business analysis apparatus according to claim 1,
The business content estimation unit includes a first time period in which the user's business content is not estimated, the first time zone in which the user has accessed the first data from the operation log information, and the user's business content For the second time zone in which it is specified that the user has accessed the second data from the operation log information, the commonality of the location of the first data and the location of the second data is If it is determined that there is commonality between the two, the business content in the second time zone in which the business content has been estimated is used as the business content of the user in the first time zone in which the business content is not estimated. presume,
Business analysis device. The business analysis device according to claim 5,
The first data and the second data are files,
The business content estimation unit determines that the first data and the second data are common to each other when the first data and the second data are stored in a folder within a preset number of close degrees,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
Store a correspondence table that includes information that associates keywords with work contents,
The business content estimation unit acquires information on data that the user has accessed in a certain time period from the operation log information, and the acquired information includes the keyword of the correspondence table, The business content stored in association with the keyword is estimated to be the business content performed by the user during the time period,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
Store a correspondence table that includes information that associates keywords with work contents,
The business content estimation unit acquires information on the schedule of the user in a certain time zone from the schedule information, and if the acquired information includes the keyword of the correspondence table, the business content estimation unit associates the keyword with the keyword Estimating the stored business content as the business content performed by the user during the time period,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
From the operation log information or the schedule information, a word that is commonly included in the data accessed by the user in each of a plurality of time zones in which the same job content has been estimated is extracted, and the extracted word is used as the keyword. A keyword learning unit is added to the correspondence table in association with the estimated business content,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
The business content estimation unit is configured to determine a first time zone in which the user business content is estimated as the first business content based on the operation log information, and the user business content based on the operation log information. When the second time zone estimated as the work content of 2 overlaps at least in a part of the time zone, the time when the business content estimated for the time zone in which the update is performed is overlapped Estimate as work content in the belt,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
The business content estimation unit has estimated a first business time in which the first business content has been estimated from the operation log information, and a second business content different from the first business content from the schedule information. When the second time zone overlaps at least in a part of the time zone, the second business content is estimated as the business content in the overlapping time zone,
Business analysis device. The business analysis device according to any one of claims 1 to 6,
Based on the time width of each time zone and the business content of the user estimated for each time zone, information indicating the accumulated time for each business content of the user is generated,
Business analysis device. Information processing device
Storing operation log information that is information related to an operation history of the information processing apparatus of a user who operates the information processing apparatus and schedule information that is information related to the user's work schedule;
Based on at least one of the operation log information and the schedule information, estimating and storing work contents performed by the user for each time zone, and
At least one of the operation log information and the schedule information, and the time when the user's business content is estimated by the business information and the schedule information in the time zone when the user's business content is estimated by the operation log information Estimating the business content of the user in a time zone when the business content is not estimated based on at least one of the business content in the belt,
Business analysis method to execute. The business analysis method according to claim 13,
Information processing device
From the operation log information, first information that is information related to data accessed by the user in a first time zone in which the user's business content has not been estimated, and a second time in which the user's business content has been estimated. Obtaining second information that is information relating to data that the user has accessed in a band; and
When the second information is included in the first information, the business content in the second time zone in which the business content of the user has been estimated is represented by the first time zone in which the business content is not estimated. Estimating the user's business content;
Is a business analysis method. The business analysis method according to claim 13,
Information processing device
The user's business content is not estimated, and the user is informed by the schedule information within a preset time range from the first time zone in which it is understood from the operation log information that the user has accessed the data. If there is a second time zone in which the business content of the user has been estimated, the step of estimating the business content in the second time zone as the business content of the user in the first time zone in which the business content is not estimated,
Is a business analysis method.

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