JP2012043043A - Information processor and information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processor, when there are persons, though belonging to a same organization, behave in a different manner, preventing seats from being arranged in such a manner as gathering persons in the same organization including the aforementioned persons.SOLUTION: Classification means of the information processor classifies the persons in the organization into a first group and a second group based on behavior information, or a record of the past behavior of the persons in the organization; similarity acquisition means acquires a first group of another organization whose behavior record is similar to the behavior record of the persons of the first group classified by the classification means; and arrangement means arranges the seats such that the persons of the first group having similarity acquired by the similarity acquisition means are gathered.

Description

  The present invention relates to an information processing apparatus and an information processing program.

  Patent Document 1 relates to an office specification determination apparatus and an office layout generation apparatus, and determines the optimal office fixtures and information equipment equipment based on the characteristics of work performed in the office, and performs an optimal layout. For that purpose, input or measure the characteristic information on the work of the personnel engaged in the office, determine the work style based on the characteristic information of the work, information on the basic equipment and the characteristic information of the work on the determined work style Based on the above, the details of the basic equipment are refined according to the business characteristics, the equipment required for the office is determined, and each equipment is arranged in the office based on the floor plan information etc. It is disclosed that the zoning determination of whether or not it is possible is performed and the layout of the zone and each equipment is performed.

  Patent Document 2 has an object to provide a layout determination apparatus capable of determining an office layout with reduced environmental load, and responds to a request for office layout determination from a client terminal connected via a network. In the layout determination server that determines the layout of the office, the layout determination server sends information about the office (the name of the office, the department name assigned to the office, and the personnel of each department, which are sent from the client terminal. Based on the number of working hours of each department placed in the corresponding office from the working hours DB that stores information on the working hours of each department placed in each office. Based on the information on the working hours of each department that has been searched, the layout of the relevant office with reduced environmental impact is determined, and the client It is disclosed to be sent to preparative terminal.

  Patent Document 3 has an object to provide an office layout plan support apparatus, an office layout plan support method, and an office layout plan support program that can make a layout plan that can efficiently perform work performed after moving in. For each combination of two departments in a department, mutual proximity between the combined departments and mutual similarity are derived, and for each combination of two departments in the plurality of departments based on the mutual proximity and the mutual similarity. The set proximity indicating the degree of close placement is derived, the placement positions between the departments are brought close to each other in descending order of the set proximity, and the required floor area indicated by the required floor area information is indicated by the allowable floor area information. The multiple departments are placed in the building so as to fit within the allowable floor area. Be displayed are disclosed in Ant device.

  In Patent Document 4, it is an object to make it possible to change the layout of a shared booth, shared equipment, or a user's seat to a more efficient position for the user. The position of the mobile terminal is specified by the means, the movement information for each mobile terminal is specified by the movement path specifying means using the history information, and the positions of the facilities commonly used by the user are a plurality of mobile terminals. Is included as the movement route arrival position information, it is extracted as a change target movement route, and the change position of the equipment is obtained so that the average movement distance of the change target movement route becomes shorter.

JP 2001-184375 A JP 2004-2527779 A JP 2006-302137 A JP 2009-169633 A

  In the present invention, when there are personnel who belong to the same organization but have different behaviors, information that prevents the seats from being arranged so that the personnel of the same organization including such personnel can be gathered. An object is to provide a processing device and an information processing program.

The gist of the present invention for achieving the object lies in the inventions of the following items.
According to a first aspect of the present invention, there is provided a classification unit that classifies the personnel of the organization into a first set and a second set based on behavior information that is a record of past behaviors of the personnel in the organization, and the classification unit. Similar acquisition means for acquiring a first set of other organizations with similar behavior records of the classified first set of personnel, and the similar first set acquired by the similarity acquisition means An information processing apparatus comprising an arrangement means for arranging seats so that personnel gather.

  The invention according to claim 2 is characterized in that the arrangement means arranges the seats of the second set of members in each organization in a seat where a user is not fixed or a seat located at a boundary between organizations. The information processing apparatus according to Item 1.

  According to a third aspect of the present invention, the classifying means compares behavior information, which is a record of past behavior of personnel of an organization, with information transmission information, which is a record of past information transmission of the personnel, so that the personnel can take a seat. The information processing apparatus according to claim 1, wherein a day not to be used is calculated, and the personnel on the day are classified into the second set.

  The invention according to claim 4 is the information processing apparatus according to any one of claims 1 to 3, wherein the action information is a record of actions in each continuous time zone.

  The invention of claim 5 classifies the computer into a first set and a second set based on behavior information that is a record of past behavior of personnel in the organization, and Similar acquisition means for acquiring a first set of other organizations with similar behavior records of the first set of persons classified by the classification means, and similar first acquired by the similarity acquisition means It is an information processing program for making it function as an arrangement | positioning means which arrange | positions a seat so that the member of a set of may gather.

  According to the information processing apparatus of claim 1, when there are personnel belonging to the same organization but having different behaviors, the seats are arranged so that the personnel of the same organization including such personnel gather. Can be prevented.

  According to the information processing apparatus of the second aspect, a person who belongs to the same organization but has different behavior can be placed in a seat where a user is not fixed or a seat located at a boundary between organizations.

  According to the information processing apparatus of the third aspect, on the day when the staff does not use the seat, the staff can be classified into the second set.

  According to the information processing apparatus of the fourth aspect, compared to the case where only the attendance time and the departure time are determined, it is possible to target behavior information due to going out in which a so-called hollow out occurs.

  According to the information processing program of claim 5, when there are personnel who belong to the same organization but have different behaviors, the seats are arranged so that personnel of the same organization including such personnel gather. Can be prevented.

It is a conceptual module block diagram about the structural example of this Embodiment. It is explanatory drawing which shows the system configuration example at the time of embodying this Embodiment. It is explanatory drawing which shows the example of a data structure of an action log table. It is explanatory drawing which shows the data structure example of a communication log table. It is explanatory drawing which shows the data structure example of an organization information table. It is explanatory drawing which shows the example of a data structure of a work phase data table. It is explanatory drawing which shows the example of a data structure of a seat information table. It is explanatory drawing which shows the example of a data structure of a determination result table. It is explanatory drawing which shows the example of a data structure of a prediction result table. It is a flowchart which shows the production process example of the performance data by this Embodiment. It is explanatory drawing which shows the process example by this Embodiment. It is a block diagram which shows the hardware structural example of the computer which implement | achieves this Embodiment.

Hereinafter, an example of a preferred embodiment for realizing the present invention will be described with reference to the drawings.
FIG. 1 shows a conceptual module configuration diagram of a configuration example of the present embodiment.
The module generally refers to components such as software (computer program) and hardware that can be logically separated. Therefore, the module in the present embodiment indicates not only a module in a computer program but also a module in a hardware configuration. Therefore, the present embodiment is a computer program for causing these modules to function (a program for causing a computer to execute each procedure, a program for causing a computer to function as each means, and a function for each computer. This also serves as an explanation of the program and system and method for realizing the above. However, for the sake of explanation, the words “store”, “store”, and equivalents thereof are used. However, when the embodiment is a computer program, these words are stored in a storage device or stored in memory. It is the control to be stored in the device. Modules may correspond to functions one-to-one, but in mounting, one module may be configured by one program, or a plurality of modules may be configured by one program, and conversely, one module May be composed of a plurality of programs. The plurality of modules may be executed by one computer, or one module may be executed by a plurality of computers in a distributed or parallel environment. Note that one module may include other modules. Hereinafter, “connection” is used not only for physical connection but also for logical connection (data exchange, instruction, reference relationship between data, etc.). “Predetermined” means that the process is determined before the target process, and not only before the process according to this embodiment starts but also after the process according to this embodiment starts. In addition, if it is before the target processing, it is used in accordance with the situation / state at that time or with the intention to be decided according to the situation / state up to that point.
In addition, the system or device is configured by connecting a plurality of computers, hardware, devices, and the like by communication means such as a network (including one-to-one correspondence communication connection), etc., and one computer, hardware, device. The case where it implement | achieves by etc. is also included. “Apparatus” and “system” are used as synonymous terms. Of course, the “system” does not include a social “mechanism” (social system) that is an artificial arrangement.
In addition, when performing a plurality of processes in each module or in each module, the target information is read from the storage device for each process, and the processing result is written to the storage device after performing the processing. is there. Therefore, description of reading from the storage device before processing and writing to the storage device after processing may be omitted. Here, the storage device may include a hard disk, a RAM (Random Access Memory), an external storage medium, a storage device via a communication line, a register in a CPU (Central Processing Unit), and the like.

  As illustrated in the example of FIG. 1, the information processing apparatus 100 according to the present embodiment includes an individual behavior pattern determination / prediction module 130, a layout determination module 140, a reception module 170, and an output module 180. The information processing apparatus 100 is connected to the behavior log data storage module 110, the communication log data storage module 120, the organization information storage module 150, and the seat information storage module 160. Users are called personnel, employees, etc. depending on the context.

  The behavior log data storage module 110 is connected to the individual behavior pattern determination / prediction module 130. The action log data storage module 110 stores action information (hereinafter also referred to as action log data) that is a record of past actions. The “behavior” is an action that can be observed by the target user, and includes at least entering and leaving the room where the target seat is located. “Behavior information that is a record of past behavior” refers to information (hereinafter, also referred to as behavior log data) that records the behavior of a target user in the past. For example, when an electronic tag possessed by a user is detected by sensors arranged in various places, the position of the sensor (sensor ID (IDentification) indicating the sensor and the position of the sensor are uniquely associated) May be a sensor ID), and the user ID indicating the user stored in the detected electronic tag is recorded together with the detection time. The action log data storage module 110 stores, for example, an action log table 300. FIG. 3 is an explanatory diagram showing an example of the data structure of the action log table 300. The action log table 300 includes a start time column 310, an end time column 320, an employee ID column 330, and an area column 340. The start time column 310 stores the date and time when the user of the employee ID column 330 enters the room of the area column 340. The end time column 320 stores the date and time when the user in the employee ID column 330 leaves the room in the area column 340. The employee ID column 330 stores user information indicating the target user. For example, an employee ID. The area column 340 stores area information indicating the target area. For example, the conference room name. Also, the behavior information stored in the behavior log data storage module 110 may be a record of behavior indoors, or may include a record of behavior outdoors.

  The communication log data storage module 120 is connected to the individual behavior pattern determination / prediction module 130. The communication log data storage module 120 stores information transmission information that is a record of past information transmission. “Information transmission” is communication by e-mail or the like. “Information transmission information that is a record of past information transmission” refers to information (hereinafter also referred to as communication log data) that records past communications with others. The communication log data storage module 120 stores a communication log table 400, for example. FIG. 4 is an explanatory diagram showing an example of the data structure of the communication log table 400. The communication log table 400 includes a transmission time column 410, a transmission employee ID column 420, a reception employee ID collection column 430, a received mail address collection column 440, and a size column 450. The transmission time column 410 stores the date and time when the electronic mail is transmitted. The outgoing employee ID column 420 stores user information indicating the user who sent the electronic mail. For example, an employee ID. The reception employee ID set column 430 stores user information indicating a user who has received the electronic mail. A plurality of user information may be stored. The received mail address set column 440 stores the mail address of the user who received the electronic mail. A plurality of mail addresses may be stored. The size column 450 stores the size (capacity) of the electronic mail.

  The organization information storage module 150 is connected to the individual behavior pattern determination / prediction module 130 and the layout determination module 140. The organization information storage module 150 stores correspondence between user information indicating a user and organization information indicating an organization to which the user belongs. The user may also store free address application information indicating whether or not a seat to which the user is not fixed (hereinafter also referred to as a free address) may be applied. The organization information storage module 150 stores, for example, an organization information table 500 and a business phase data table 600. FIG. 5 is an explanatory diagram showing an example of the data structure of the organization information table 500. The organization information table 500 has an employee ID column 510, a belonging organization column 520, a free address application column 530, and a customer domain column 540. The employee ID column 510 stores user information indicating a user. For example, an employee ID. The organization column 520 stores organization information indicating the organization to which the user belongs. For example, the name of the organization. The free address application column 530 stores free address application information indicating whether or not the user can apply a free address. The customer domain column 540 stores the domain name of the person (for example, customer) with whom the user is working together.

  Further, the business phase data table 600 stores a progress status (business phase) of a business performed by the user. Thereby, it is possible to acquire a business in which the user is involved, and to acquire a period during which the business is being performed (which may be a period during which the business has been performed, hereinafter the same). FIG. 6 is an explanatory diagram showing an example of the data structure of the business phase data table 600. The business phase data table 600 has an employee ID column 610, a period column 620, and a business phase column 630. The employee ID column 610 stores user information indicating a user. For example, an employee ID. The period column 620 stores a period during which the business phase is performed. The business phase column 630 stores business phase information indicating a business phase. For example, the name of the business phase.

  The seat information storage module 160 is connected to the layout determination module 140. The seat information storage module 160 stores the seat information indicating the seat in the room and the user information indicating the user assigned to the seat in association with each other. The seat information storage module 160 stores a seat information table 700, for example. FIG. 7 is an explanatory diagram showing an example of the data structure of the seat information table 700. The seat information table 700 has a seat ID column 710, a floor column 720, a coordinate column 730, a free address seat column 740, and an assigned employee ID column 750. The seat ID column 710 stores seat information indicating a seat. The floor column 720 stores floor information indicating the floor on which the seat is located. The coordinate column 730 stores the position of the seat. For example, the coordinates in the XY coordinate system. The free address seat column 740 stores free address seat information indicating whether or not the seat can be a free address. The assigned employee ID column 750 stores user information indicating a user assigned to the seat. That is, this user is seated in the seat.

The individual behavior pattern determination / prediction module 130 is connected to the behavior log data storage module 110, the communication log data storage module 120, the layout determination module 140, and the organization information storage module 150. The individual behavior pattern determination / prediction module 130 is stored in the behavior log data stored in the behavior log data storage module 110, the communication log data stored in the communication log data storage module 120, and the organization information storage module 150. Based on the organization information, the behavior pattern is determined and predicted for each user. For example, a behavior pattern is determined based on behavior log data stored in the behavior log data storage module 110. For example, based on the action log data stored in the action log data storage module 110, the communication log data stored in the communication log data storage module 120, and the organization information stored in the organization information storage module 150, the user Predict behavior patterns every time.
Detailed processing contents of the behavior pattern and individual behavior pattern determination / prediction module 130 will be described later.

  The layout determination module 140 is connected to the individual behavior pattern determination / prediction module 130, the organization information storage module 150, the seat information storage module 160, the reception module 170, the display module 182 of the output module 180, and the notification module 184. Based on the request received by the receiving module 170, the layout determination module 140 determines the organization information stored in the organization information storage module 150, the seat information stored in the seat information storage module 160, and the individual behavior pattern determination / prediction. The seat layout is determined using the information determined and predicted by the module 130.

The layout determination module 140 classifies the personnel in the organization into set A and set B based on the behavior patterns determined by the individual behavior pattern determination / prediction module 130. Which set the user belongs to is determined for each organization. The set A is a set of persons who perform an average action in the organization. The set B is a set of persons who do not belong to the set A in the organization and includes a person who deviates from the behavior pattern tendency of the organization, a person whose behavior is not consistent, and the like. The classification into the set A and the set B uses the action log data stored in the action log data storage module 110 via the action pattern. That is, the layout determination module 140 classifies the personnel of the organization into a set A and a set B based on behavior information that is a record of past behaviors of personnel in the organization.
In addition, the layout determination module 140 compares the action log data stored in the action log data storage module 110 with the communication log data stored in the communication log data storage module 120 to determine whether the target person is seated. A day (for example, a day when the user is out) may be calculated and the number of persons on that day may be classified into the set B.

  The layout determination module 140 acquires the first behavior pattern of another organization in which the behavior records of the personnel of the first behavior pattern classified by the individual behavior pattern determination / prediction module 130 are similar. Then, the seats are arranged so that the personnel having the similar first action pattern gather. This is not simply placing an organization with similar behavior patterns in organizational units in the vicinity, but includes those who deviate from the behavior pattern tendency of the organization, those who have inconsistent behavior patterns, etc. Those who have the behavior pattern are excluded, and other organizations with similar behavior patterns are obtained.

“Arranging seats” refers to associating seat information indicating a seat with user information indicating a user who uses the seat.
A seat in which persons having similar behavior patterns are gathered may be a seat in an area where lighting equipment or air conditioning equipment can be adjusted. This is to make it easy to perform collective power control and reduce the environmental load by using a seat that collects persons with similar behavior patterns. “Area where lighting equipment or air-conditioning equipment can be adjusted” means that one or more lighting equipment or air-conditioning equipment is installed in that area, and that the lighting equipment or air-conditioning equipment in that area is turned on or off. Is possible independently of (independent of) lighting equipment or air conditioning equipment in other areas. The adjustment of the lighting device includes, for example, adjustment of brightness, hue, and the like, and the adjustment of the air conditioning device includes, for example, adjustment of temperature, air volume, and the like.

In addition, the layout determination module 140 may arrange the seats of the personnel of the second behavior pattern in each organization in a free address seat or a seat located at the boundary between organizations. The first action pattern is arranged in a different seat.
The detailed processing contents of the layout determination module 140 will be described later.

The reception module 170 is connected to the layout determination module 140. The reception module 170 receives a layout generation request instruction, and instructs the layout determination module 140 to issue a layout generation request. This instruction may be performed periodically (for example, once a day when the first user's entry is detected), or may receive a user's instruction operation.
The output module 180 includes a display module 182 and a notification module 184. The output module 180 outputs the seat layout determined by the layout determination module 140.
The display module 182 is connected to the layout determination module 140. The display module 182 displays the layout determined by the layout determination module 140. For example, the information may be displayed graphically on a display device such as a display provided in the information processing apparatus 100. In addition, each time a corresponding user enters the room, the seat of that person may be displayed on a panel provided in an entry / exit detection device that detects the entry / exit of the user. Further, the corresponding seat may be output by voice.
The notification module 184 is connected to the layout determination module 140. The notification module 184 notifies a user who uses a seat with a free address whose seats can be dynamically changed using an electronic mail or the like as to which seat to go to.

FIG. 2 is an explanatory diagram showing a system configuration example when the present embodiment is embodied.
A log DB server host 230, a layout server host 240, a position information server host 270, and a layout client host 280 are connected via a communication line 299. In addition, an action log DB 210 and a communication log DB 220 are connected to the log DB server host 230, an information processing apparatus 100 is connected to the layout server host 240, and an organization information DB 250 is connected to the information processing apparatus 100. The seat information DB 260 is connected, and the position information server host 270 is connected with position sensors 271 to 278. Compared to the module configuration illustrated in FIG. 1, the action log DB 210 corresponds to the action log data storage module 110, the communication log DB 220 corresponds to the communication log data storage module 120, and the organization information DB 250 corresponds to the organization information storage module 150. The seat information DB 260 corresponds to the seat information storage module 160. In addition, the reception module 170 and the output module 180 in the information processing apparatus 100 receive an instruction operation or the like to the layout client host 280 by the user 200, perform display on the layout client host 280, output of notification, and the user. Inform 200 about your seat.

  The user 200 has a tag 201. The tag 201 is detected by the position sensors 271 to 278. Each position sensor reads the user information (for example, employee ID (IDentification)) indicating the user stored in the tag 201, and stores it in the position information server host 270 together with the detected date and time, and the position of the position sensor itself. The For example, when a position sensor is attached to each room, it is collected by the position information server host 270 as action log data indicating who is in which room and when. Then, the collected action log data is transferred to the log DB server host 230, and the action log table 300 illustrated in FIG. 3 is stored in the action log DB 210.

Further, the user 200 uses the layout client host 280 and the like to send and receive electronic mail. The log DB server host 230 collects e-mail transmission / reception logs, and stores the communication log table 400 illustrated in FIG. 4 in the communication log DB 220. The transmission / reception log may be acquired from a mail server.
The layout client host 280 receives an operation instruction from the user 200, passes the operation instruction to the layout server host 240, and causes the information processing apparatus 100 to determine the layout. The information processing apparatus 100 determines the layout using the data in the action log DB 210, the communication log DB 220, the organization information storage module 150, and the seat information storage module 160, and lays out the layout client host 280 via the layout server host 240. The result is displayed and notified to inform the user 200.

The process of the individual behavior pattern determination / prediction module 130 will be described.
First, the determination process will be described.
The probability of detection by an indoor position sensor is obtained for each successive time period and used as a vector. This vector is called a “detection probability vector”. This represents an individual's behavior pattern. The time zone here means a period from A to B, for example, every 1 hour, every 2 hours, every 30 minutes, or from 9 am to 5 pm Between is every 30 minutes, and every other hour may be between. Hereinafter, every hour starting from midnight is illustrated as a continuous time zone.
An average value of detection probability vectors on business days within a predetermined period in the past is calculated for each individual and used as a determination result. The determination result is, for example, a determination result table 800. FIG. 8 is an explanatory diagram showing an example of the data structure of the determination result table 800. The determination result table 800 has an employee ID column 810 and a detection probability vector column 820. The employee ID column 810 stores an employee ID indicating an employee. The detection probability vector column 820 stores the detection probability vector of the employee.

The determination process will be described in more detail.
A detection probability vector P (ID, d) is defined as follows for the detection results in indoor behavior on the date d of the employee indicated by the employee ID, and this is defined as an individual behavior pattern.
Detection probability vector P (ID, d) = [P (ID, d, 0), P (ID, d, 1), ..., P (ID, d, 23)]
The determination of the action pattern here generates a detection probability vector P.
Each element P (ID, d, t) in this definition formula represents the detection probability at the time t at the date d of the employee indicated by the employee ID. The time zone here is every hour. That is, when the number of seconds detected indoors between time ts and time te on the date d of the employee indicated by the employee ID is represented by T (ID, d, ts, te), each element P of the detection probability vector is ( 1) It is defined like the formula. In addition, when te is 24, it represents 0 o'clock on the next day of date d. 3600 is the number of seconds for one hour.

T is generated from the action log table 300.
The detection probability vector for a specific area type may be defined by limiting the detection range of T to a specific area type such as a conference room instead of the entire indoor area.

Next, the prediction process by the individual behavior pattern determination / prediction module 130 will be described. Here, the prediction is to predict a day when a person does not use a seat. As a day when the seat is not used, an example of going out will be mainly described.
The communication log table 400 is used to measure the amount of change in mail volume with customers and employees at other business locations, and the lag between the peak time and the “outing judgment date” that appears after that (day difference)
Is calculated in advance. The “outing determination date” is extracted by comparing the value of a predetermined time zone of the detection probability vector with a predetermined threshold value. The predetermined time zone corresponds to a working time zone, for example. The comparison with the threshold value is a determination as to whether or not the value of the detection probability vector is less than the threshold value.

When it is determined that a mail volume peak has occurred, a predetermined range centered on a pre-calculated lag is predicted as “a day when going out is likely to occur”, and detection probabilities observed at that lag in the past The average of vectors is output as a predicted value.
When the prediction is established, the prediction result is output. The prediction result is, for example, a prediction result table 900. FIG. 9 is an explanatory diagram showing an example of the data structure of the prediction result table 900. The prediction result table 900 has an employee ID column 910, a detection probability vector column 920, and a prediction date column 930. The employee ID column 910 stores an employee ID indicating an employee. The detection probability vector column 920 stores the “average of detection probability vectors observed at the past lag” of the employee. The predicted date column 930 stores the “day when the employee is likely to go out” of the employee.

The prediction process will be described in more detail. Here, a process for predicting a case where an employee who does not normally go out only for a certain period will be described as an example.
First, based on a past communication log (communication log table 400 in the communication log data storage module 120) and an indoor action log (behavior log table 300 in the action log data storage module 110), the basis of prediction is “ "Result data" is created.
“Result data” is created as follows.
Distribution of lag (number of days) of the employee indicated by the employee ID from the day that is the “outing judgment date” after e-mail transmission to the customer domain (customer domain column 540 of the organization information table 500) reaches its peak. And the ternary set <ID, P ^* , δ ^* > consisting of the employee ID, the mode lag δ ^* , and the average value P ^* of the detection probability vectors at the mode lag is used as the actual data.

FIG. 10 is a flowchart illustrating an example of a process for creating performance data by the individual-specific behavior pattern determination / prediction module 130 according to the present embodiment.
In step S1002, a set D of customer domains corresponding to the employee ID is acquired from the organization information.
In step S1004, a unit period in which the amount of mail transmitted within one unit period for any domain in the set D is maximized is extracted, and the center date of each unit period is substituted into the set A.
In step S1006, a date d in which the detection probability of the “daytime (within working hours)” detection probability vector P (ID, d) falls below a predetermined threshold is extracted and substituted into set B.
In step S1008, the result list X is emptied.

In step S1010, it is determined whether or not the set A is empty. If it is empty, the process proceeds to step S1016. Otherwise, the process proceeds to step S1012.
In step S1012, an arbitrary date d is extracted from set A and deleted from set A.
In step S1014, if a date after date d exists in set B, date d ′ closest to date d is extracted from set B, and binomial set <d′−d, P (ID, d ′)> is obtained. Add to achievement list X.
In step S1016, in the performance list X, the number of binomial groups <δ, P> is counted for each value of δ, and an average P ^* of P is obtained for δ ^{* having the} largest number of cases, and <ID, P ^* , δ ^* > Is the actual value.

The actual data <ID, P ^* , δ ^* > is “The employee indicated by the employee ID is most likely to go out after δ ^* days after sending many emails to the customer, and the behavior pattern of the day is closest to P ^*. ".
In the future, if there is a date d when the employee is detected to have peaked email transmission to the customer domain in the future, refer to the actual data, and the most frequent lag δ ^* days after that date d Predict that it is likely to occur, and output a prediction result <ID, P ^* , d + δ ^* > (prediction result table 900).

You may make it estimate that going out to other establishments will increase based on the mail volume to the employee who works at another establishment. The “amount of emails to employees working at other offices” is detected by the presence of the email address “employees working at other offices” in the received mail address set column 440 of the communication log table 400. The prediction process may be performed.
Further, it may be predicted that the use of the conference room will increase based on the amount of mail to people who are not usually involved in business, but are sometimes related. For example, a person who is not normally involved in business is a person who has sent an e-mail to a domain other than the customer domain field 540 of the organization information table 500, or a received mail address set field 440 of the communication log table 400. It may be determined by extracting a person whose frequency is lower than a predetermined threshold value, and the above-described prediction process may be performed.

ただし、Ｔｅｒｍ（ＩＤ）は社員番号ＩＤの分析対象期間の日付集合である。 Processing A (collective layout) of the layout determination module 140 will be described.
(A1) The layout determination module 140 holds the variation amount of the behavior pattern for each individual based on the behavior pattern for each individual delivered from the individual behavior pattern determination / prediction module 130. Specifically, for each individual, a detection probability vector for a predetermined period (from about three months to about half a year) or the period of the latest business phase in the business phase data table 600 (period column 620) is held. By calculating the variance of each element of the detection probability vector, the variation amount of the behavior pattern is obtained. The fluctuation amount Pv (ID, t) of the behavior pattern in the time zone at the time t of the employee indicated by the employee number ID is expressed by equation (2).

Here, Term (ID) is a set of dates of the analysis target period of the employee number ID.

  (A2) A layout request instruction is received from the user via the reception module 170. For example, a seat manager in the general affairs department is a user here. The layout request includes a list of organizations to be laid out and a list of layout destination floors.

(A3) Upon receiving the layout request, the layout determination module 140 compares the variation amount of the behavior pattern with a predetermined threshold value for each of the members belonging to the layout target organization (for example, the variation amount is When the threshold value is exceeded), a person whose behavior pattern is an exception is extracted and the exceptional person is excluded. Then, the representative value of the behavior pattern of the remaining personnel is obtained and set as the behavior pattern of the organization. Note that a constant may be set as the threshold value here, or a relative setting may be performed for each organization so that the top x% of the organization can be excluded. A set M ^* (G) of members belonging to the organization G that remains without being excluded when the set of members belonging to the organization G is M (G) and the threshold is Th is as shown in Equation (3).

For example, an average value of each element of the detection probability vector may be used as the representative value of the behavior pattern of the personnel remaining without being excluded. The representative value P (G, t) of the behavior pattern of the personnel remaining without being excluded in the organization G is defined as the following equation (4). A vector P (G) = (P (G, 0), P (G, 1),..., P (G, 23)) defined based on this is used as a representative action pattern of the organization G. .

(A4) The layout determination module 140 performs clustering based on the similarity of the behavior patterns of each organization, and arranges similar organizations on the same floor within a range that satisfies the constraint condition of the number of seats. Similarity is defined by a distance function (for example, Euclidean distance) between detection probability vectors. The similarity R (G ₁ , G ₂ ) of the behavior patterns of the organizations G ₁ and G ₂ is defined as the equation (5). Note that || x || is the magnitude of the vector x.

Using this, if the set of all organizations is G ^* , the set of all floors is F ^* , the mapping from the floor F to the set of organizations assigned to that floor is A, and the number of seats on the floor F is C (F), This is an optimization problem for obtaining mapping A under the condition of equation (6). Map A can be found by brute force from among possible combinations. Once the organization assignment to each floor is determined, the actual seat assignment may be determined by an existing geometric layout algorithm. The function V (G ₁ , G ₂ ) is defined by the layout execution entity according to the business situation, and gives a loss value when the organization G ₁ and the organization G ₂ are not arranged on the same floor. The weights w ₁ and w ₂ are set according to how much the layout execution entity places importance on R or V when performing layout. For example, when the weight w ₁ is increased, the organization with a similar behavior pattern is preferentially placed on the same floor (eco-oriented setting), and when the weight w ₂ is increased, the organization that should be close to work is preferentially placed on the same floor. Arranged (business-oriented setting).

(A5) In the above-described procedure (A3), personnel excluded as exceptional personnel that deviate from the organizational behavior pattern are handled as follows. By this process, exceptional personnel perform a special arrangement that allows local power control.
If the attribute of the excluded personnel is “no free address” (free address application field 530 of the organization information table 500), the layout is made within each organization, but is preferentially placed near the boundary between the organizations.
If the attribute of the excluded person is “free address available” (free address application field 530 of the organization information table 500), the attribute is placed in an area set as a free address. In that case, the free address placement target person may also perform clustering based on the similarity of the action patterns to collect personnel having similar action patterns.
(A6) The layout determination module 140 outputs the layout determined through the above procedure to the user via the output module 180.

Next, processing B (navigation to personnel whose behavior pattern changes) of the layout determination module 140 will be described.
(B1) The layout determination module 140 compares the variation amount of the individual behavior pattern passed from the individual behavior pattern determination / prediction module 130 with a predetermined threshold value (for example, when the variation amount exceeds the threshold value). ) When an exceptional personnel is detected, the personnel is notified via the notification module 184.
・ If the attribute of the person concerned is “no free address” (free address application field 530 of the organization information table 500), a message such as “Let's consider the environment” is notified, and the person concerned is relative to the seat. Shows a message to the effect that he / she is aware that he / she is working with a high environmental load.
If the attribute of the person is “free address is possible” (free address application field 530 of the organization information table 500), in addition to the above-described message, notification of free address seats is notified.

(B2) The layout determination module 140 notifies the personnel notified of the behavior pattern change prediction from the individual behavior pattern determination / prediction module 130 via the notification module 184.
-If the attribute of the employee is “No free address” (free address application field 530 in the organization information table 500), a message such as “Let's forget to turn off the electrical equipment when going out” is notified. A message to the effect that the person concerned is aware of measures necessary for reducing the environmental load that is often forgotten because the person is different from the usual behavior pattern.
If the attribute of the person is “free address is possible” (free address application field 530 of the organization information table 500), the user is guided to move to a free address appropriate for the predicted behavior pattern. For example, it guides you to a free address seat that gathers people who frequently go out. As a result, many of these seats are vacant during working hours, so that it is easy to transfer power to other purposes such as power control in a lump or meeting with an indoor residual person, thereby improving environmental efficiency.

Next, processing C (free address layout) of the layout determination module 140 will be described.
First, the free address layout will be described. In the free address floor 1100 illustrated in FIG. 11, a set of free address seats (free address seats 1111-1116, etc.) (zones 1110, 1120, 1130, 1140, 1150, lighting equipment or air conditioning equipment can be adjusted. In some cases, it is possible to finely control the power in units). In order to appropriately lay out the persons assigned to the free addresses, the layout should be such that the behavior patterns are similar in the zone and the number of used zones × the usage time is minimized. Furthermore, for business efficiency, it is necessary to make each individual organization arranged in the same zone as homogeneous as possible.

It is assumed that the layout of the free address is reviewed every day, and shows a procedure (process C) for determining the layout of the current day collectively.
(C1) The typical value of the action pattern is calculated for each individual for the most recent date set Term. As a typical value, each element of the detection probability vector is averaged in the term date set. The typical value P _T (ID, t) of the employee in the time zone t indicated by the employee ID is defined as shown in the equation (7), and a vector PT (ID) = (P _T (ID, _t 0), P _T (ID, 1),..., P _T (ID, 23)) are typical values of the employee number ID.

(C2) In the personnel set M, the maximum detection rate P _H (M, t) (formula (8)) in the time zone t is calculated, and the vector P _H (M) = (P _H (M, 0), P _H (M, 1),..., P _H (M, 23)). This vector has an expected value for each time zone in which someone in the member set M is detected as an element.

(C3) When assigning an individual to a free address, the behavior pattern for each individual in the zone is made similar, and the sum of the maximum detection rates for each zone is minimized. The former goal is to expect the maximum length of time that the zone will not be used at all if the behavior patterns are similar. The latter goal is expected to make efficient use of the entire free address. The similarity R (ID ₁ , ID ₂ ) of the behavior pattern for each individual is defined as in equation (9). Note that || x || is the magnitude of the vector x.

(C4) Using this, when the set of the entire zone is Z ^* , the mapping from the zone Z to the set of individual employee IDs assigned to the zone is A ′, and the number of seats in the zone Z is C (Z). Then, it becomes the optimization problem which calculates | requires mapping A 'on condition of (10) Formula. Map A ′ can be found by brute force from among possible combinations. If the assignment of individuals to each zone is determined, specific seats may be set randomly from within the zone, or determined in the order of arrival. The function H (X) is a function for evaluating the “homogeneity” of the belonging organization with respect to the set X of employee IDs. For example, the number of types of the belonging organization can be used. The weights w ₁ and w ₂ are set in accordance with how much importance is placed on the use efficiency or the business efficiency by the layout execution entity. For example, when the weight w ₁ is increased, individuals with similar behavior patterns are preferentially placed in the same zone (eco-oriented setting), and when the weight w ₂ is increased, individuals in the same department are placed in the zone as much as possible ( Business-oriented setting).

  (C5) The layout determination module 140 outputs the layout determined through the above procedure to the user via the output module 180.

  Note that the hardware configuration of the computer on which the program according to the present embodiment is executed is a general computer as illustrated in FIG. 12, specifically, a personal computer, a computer that can be a server, or the like. That is, as a specific example, the CPU 1201 is used as a processing unit (calculation unit), and the RAM 1202, the ROM 1203, and the HD 1204 are used as storage devices. For example, a hard disk may be used as the HD 1204. A CPU 1201 for executing programs such as the individual behavior pattern determination / prediction module 130 and the layout determination module 140; a RAM 1202 for storing the programs and data; a ROM 1203 for storing a program for starting the computer; Connected to an HD 1204 as an auxiliary storage device, a receiving device 1206 that receives data based on user operations on a keyboard, mouse, touch panel, etc., an output device 1205 such as a CRT or liquid crystal display, and a communication network such as a network interface card And a bus 1208 for connecting and exchanging data. A plurality of these computers may be connected to each other via a network.

Among the above-described embodiments, the computer program is a computer program that reads the computer program, which is software, in the hardware configuration system, and the software and hardware resources cooperate with each other. Is realized.
Note that the hardware configuration shown in FIG. 12 shows one configuration example, and the present embodiment is not limited to the configuration shown in FIG. 12, but is a configuration that can execute the modules described in the present embodiment. I just need it. For example, some modules may be configured by dedicated hardware (for example, ASIC), and some modules may be in an external system and connected via a communication line. A plurality of systems shown in FIG. 5 may be connected to each other via communication lines so as to cooperate with each other. In particular, in addition to personal computers, information appliances, copiers, fax machines, scanners, printers, and multifunction machines (image processing apparatuses having two or more functions of scanners, printers, copiers, fax machines, etc.) Etc. may be incorporated.

The program described above may be provided by being stored in a recording medium, or the program may be provided by communication means. In that case, for example, the above-described program may be regarded as an invention of a “computer-readable recording medium recording the program”.
The “computer-readable recording medium on which a program is recorded” refers to a computer-readable recording medium on which a program is recorded, which is used for program installation, execution, program distribution, and the like.
The recording medium is, for example, a digital versatile disc (DVD), which is a standard established by the DVD Forum, such as “DVD-R, DVD-RW, DVD-RAM,” and DVD + RW. Standard “DVD + R, DVD + RW, etc.”, compact disc (CD), read-only memory (CD-ROM), CD recordable (CD-R), CD rewritable (CD-RW), Blu-ray disc ( Blu-ray Disc (registered trademark), magneto-optical disk (MO), flexible disk (FD), magnetic tape, hard disk, read-only memory (ROM), electrically erasable and rewritable read-only memory (EEPROM), flash Includes memory, random access memory (RAM), etc. .
The program or a part of the program may be recorded on the recording medium for storage or distribution. Also, by communication, for example, a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a wired network used for the Internet, an intranet, an extranet, etc., or wireless communication It may be transmitted using a transmission medium such as a network or a combination of these, or may be carried on a carrier wave.
Furthermore, the program may be a part of another program, or may be recorded on a recording medium together with a separate program. Moreover, it may be divided and recorded on a plurality of recording media. Further, it may be recorded in any manner as long as it can be restored, such as compression or encryption.

DESCRIPTION OF SYMBOLS 100 ... Information processing apparatus 110 ... Action log data storage module 120 ... Communication log data storage module 130 ... Individual action pattern determination / prediction module 140 ... Layout determination module 150 ... Organization information storage module 160 ... Seat information storage module 170 ... Reception module 180 ... Output module 182 ... Display module 184 ... Notification module

Claims (5)

Classification means for classifying the personnel of the organization into a first set and a second set based on behavior information that is a record of past behavior of personnel in the organization;
Similar acquisition means for acquiring a first set of other organizations with similar behavior records of the first set of personnel classified by the classification means;
An information processing apparatus comprising: an arrangement unit that arranges seats so that personnel of a first set that are similar and acquired by the similarity acquisition unit gather. 2. The information processing according to claim 1, wherein the arrangement means arranges the seats of the second set of personnel in each organization in a seat where a user is not fixed or a seat located at a boundary between organizations. apparatus. The classification means compares behavior information, which is a record of past behavior of personnel in the organization, with information transmission information, which is a record of past information transmission of the personnel, and calculates a day when the personnel do not use a seat, The information processing apparatus according to claim 1 or 2, wherein the personnel on the day are classified into the second set. The information processing apparatus according to any one of claims 1 to 3, wherein the action information is a record of actions in each continuous time zone. Computer
Classification means for classifying the personnel of the organization into a first set and a second set based on behavior information that is a record of past behavior of personnel in the organization;
Similar acquisition means for acquiring a first set of other organizations with similar behavior records of the first set of personnel classified by the classification means;
An information processing program for functioning as an arrangement means for arranging seats so that the first group of similar members acquired by the similarity acquisition means gather.

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