JP5014059B2 - Human network analysis system, human network analysis server, and human network analysis method - Google Patents

Description

  The present invention relates to a human network analysis system, a human network analysis server, and a human network analysis method for analyzing a human network formed between users who come and go within a predetermined area.

  For example, in a general company, there are many human groups such as business organizational units, and various human relationships among the members of each group and those that cross each group are formed. As a result, a complex human network is formed throughout the company. And in order for each employee to fully utilize this human network and enable business collaboration with unknown employees, etc., it is desirable to analyze the information of the internal human network and make it an employee's shared information .

Conventionally, as a technique for analyzing such a human network, an information management system described in Patent Document 1 below is known. This information management system collects information contacted by employees in the company and analyzes a human network between the employees.
JP 2007-26419 A

  However, in general, contact among employees in the company can be not only public meetings related to work but also contacts in private matters. Therefore, in the information management system of the above-mentioned Patent Document 1, information is collected by mixing business contacts and private contacts among employees, and public and private human networks between employees are collected. Cannot be managed separately. As a result, in this system, there is a problem that shared information including only elements of a public human network cannot be presented so as to meet the purpose of promoting cooperation between employees in business. Also, with this system, it is not possible to exclude private human network elements from shared information for privacy protection.

  In view of such a problem, an object of the present invention is to provide a human network analysis system, an analysis server, and an analysis method that can protect privacy and share a public human network.

The human network analysis system according to the present invention is an area attribute indicating an area attribute of each area included in a predetermined area in the human network analysis system for analyzing a human network formed by users coming and going in the predetermined area. An area attribute information storage means for storing information, a stay area detection means for detecting a stay area that is an area including the location of each user based on the position of each user measured in a predetermined area, and a stay area detection means the resulting stay area is based on the matched degree and area attribute information between the users, have a, a relationship intensity calculating means for calculating the relationship strength between the user, the relationship intensity calculating means, storage area attribute information By referring to the area attribute information of the means and based on the area attributes of the stay area that match between each user, the relationship strength for each area attribute The predetermined area is set as a work area that has the first area attribute and is used for work, and a second area that has the second area attribute and is used for private business. The degree of the case where the non-working area is included, and the relationship strength calculating means includes a case where the staying areas at the same time coincide with each other among the plurality of users and the matching staying area has the first area attribute. Based on the above, the strength of business relations between the users is calculated, the stay areas at the same time match among a plurality of users, and the matched stay areas have the second area attribute On the basis of the degree of personality, the relationship strength between the users outside the business is calculated.

  In this system, area attribute information indicating the area attribute of each area within a predetermined area exists and is stored in the area attribute information storage means. And the stay area detection means of this system detects the stay area of each user who comes and goes within a predetermined area. Then, the relationship strength between the users is calculated by the relationship strength calculation means based on the degree of matching of the stay areas of the users. At this time, the relationship strength calculation means can recognize the area attributes of the stay area that coincided with each other by referring to the area attribute information stored in the area attribute information storage means. Then, the relationship strength calculation means can calculate the relationship strength between users for each area attribute.

  Thus, if the relationship strength between users is calculated for each area attribute, for example, areas such as a business area used for business and an area outside business used for private business are different. For each, the strength of relationship between each user can be derived. Therefore, according to this system, it is possible to separate and organize only the public human network related to the business from the private human network. Information including only the target network can be shared among the users.

Further, in the human network analysis system of the present invention, the relationship strength calculation means refers to the area attribute information in the area attribute information storage means, and for each area attribute based on the area attributes of the stay areas that match among the users. Calculate relationship strength .

In the human network analysis system of the present invention, the predetermined area has a business area set as an area having the first area attribute and used for business, and a private area having the second area attribute. And the non-working area set as the area used by the user, and the relationship strength calculating means matches the stay areas at the same time among a plurality of users, and the matching stay area is the first. Based on the degree of having the area attribute, the personal relationship strength for business between the users is calculated.

  According to this configuration, only the case where the stay area is a work area is extracted for the degree to which a plurality of users stay in the same area at the same time, and based on the degree, the relational strength of the business between the users is calculated. Is done. Generally, the higher the degree of contact between users in a business area, the stronger the business relationship between the users. Therefore, according to the above configuration, the business relationship strength that reflects the actual situation more accurately Calculated.

Further, in this case, the relationship strength calculation means may determine whether the plurality of users have the same stay area at the same time and the matching stay area has the second area attribute. Calculate the strength of human relations outside of each other's work . According to this configuration, it is also possible to analyze the relationship strength between users outside the business.

  Specifically, the relationship strength calculating means accumulates stay history information that associates each user, the time, and the stay area of the user at the time obtained by the stay area detection means, and the stay history Based on the information, the relationship strength between the users may be calculated according to the degree to which a plurality of users stayed in the same area at the same time.

  Moreover, in the human network analysis system of this invention, a stay area detection means is good also as detecting the area where the mobile information terminal which each user hold | maintains exists as a stay area of the said user.

  According to this configuration, the user's stay area can be detected by a simple method such as detecting the position of the mobile information terminal held by the user.

In addition, the human network analysis system of the present invention is based on the human relationship strength between the users obtained by the relationship strength calculation means, and the people formed between the users in the area of the predetermined area attribute. Network display means for displaying the target network may be further provided.
In addition, the relationship strength calculation means, where N is the number of times a plurality of users have been together, and ET is the elapsed time since the last time the plurality of users were together, ,
RS = N-ET / constant
It is good also as calculating based on numerical formula.
Further, the relationship strength calculation means, where T is the total time that a plurality of users were together, and ET is the elapsed time from the last time the plurality of users were together, the relationship strength RS between the users. The
RS = T-ET / constant
It is good also as calculating based on numerical formula.

The human network analysis server according to the present invention is an area attribute indicating an area attribute of each area included in a predetermined area in the human network analysis server that analyzes a human network formed by users traveling in the predetermined area. An area attribute information storage means for storing information, a stay area detection means for detecting a stay area that is an area including the location of each user based on the position of each user measured in a predetermined area, and a stay area detection means Relationship strength calculation means for calculating the relationship strength between the users based on the degree of matching of the obtained stay areas between the users and the area attributes, the relationship strength calculation means is an area attribute information storage means Referring to the area attribute information, the relationship strength for each area attribute is calculated based on the area attributes of the stay areas that match among users The predetermined area has a first area attribute that is set as an area used for business, and a second area that has a second area attribute and is used as a private business area. The relationship strength calculating means is based on the degree of the case where the stay areas at the same time coincide with each other among the plurality of users and the matched stay areas have the first area attribute. The degree of business relationship between the users is calculated, and the degree of the case where the stay areas at the same time coincide with each other among the plurality of users and the matched stay areas have the second area attribute. Based on this, the strength of the human relationship outside the business between the users is calculated.

  In this server, area attribute information indicating the area attribute of each area in the predetermined area exists and is stored in the area attribute information storage means. And the stay area detection means of this system detects the stay area of each user who comes and goes within a predetermined area. Then, the relationship strength between the users is calculated by the relationship strength calculation means based on the degree of matching of the stay areas of the users. At this time, the relationship strength calculation means can recognize the area attributes of the stay area that coincided with each other by referring to the area attribute information stored in the area attribute information storage means. Then, the relationship strength calculation means can calculate the relationship strength between users for each area attribute.

  Thus, if the relationship strength between users is calculated for each area attribute, for example, areas such as a business area used for business and an area outside business used for private business are different. For each, the strength of relationship between each user can be derived. Therefore, according to this system, it is possible to separate and organize only the public human network related to the business from the private human network. Information including only the target network can be shared among the users.

The human network analysis method according to the present invention is an area attribute indicating an area attribute of each area included in a predetermined area in the human network analysis method for analyzing a human network formed by users who come and go within a predetermined area. An area attribute information storage step for storing information in the area attribute information storage means, and a stay area detection means detects a stay area that is an area including the location of each user based on the position of each user measured in a predetermined area. The relationship strength calculation in which the stay area detection step and the relationship strength calculation means calculate the relationship strength between the users based on the degree and area attribute that the stay areas obtained in the stay area detection step match between the users. has a step, the relation strength calculation section refers to the area attribute information of the area attribute information storage unit, each user Based on the area attributes of the stay areas that coincided with each other, the relationship strength for each area attribute is calculated, and the predetermined area has a first area attribute and is set as an area used for business, Non-working areas that are set as areas used for private business with two area attributes, and the relationship strength calculation means that the stay areas at the same time match among multiple users In addition, based on the degree of the case where the corresponding stay area has the first area attribute, the personal relationship strength for business between the users is calculated, and the stay areas at the same time among a plurality of users are calculated. It is characterized in that the strength of the personal relationship outside the business between the users is calculated based on the degree of matching and the matching stay area having the second area attribute .

  In this analysis method, area attribute information indicating the area attribute of each area in the predetermined area is stored in the area attribute information storage step. Then, in the stay area detection step, the stay area of each user who travels within the predetermined area is detected. Then, in the relationship strength calculation step, the relationship strength between the users is calculated based on the degree of matching of the stay areas of the users. At this time, in the relationship strength calculation step, the area attribute of the matched stay area can be recognized by referring to the area attribute information. In the relationship strength calculation step, the relationship strength between users can be calculated for each area attribute.

  Thus, if the relationship strength between users is calculated for each area attribute, for example, areas such as a business area used for business and an area outside business used for private business are different. For each, the strength of relationship between each user can be derived. Therefore, according to this system, it is possible to separate and organize only the public human network related to the business from the private human network. Information including only the target network can be shared among the users.

  According to the present invention, it is possible to provide a human network analysis system, an analysis server, and an analysis method capable of protecting privacy and sharing a public human network.

  DESCRIPTION OF EMBODIMENTS Hereinafter, a preferred embodiment of a human network analysis system, an analysis server, and an analysis method according to the present invention will be described in detail with reference to the drawings.

  As shown in FIGS. 1 and 2, the human network analysis system 1 is a system for analyzing a human network formed by employees who come and go in the floor F of the company. The human network analysis system 1 includes a positioning system 3 that measures the position of the employee in the floor F, and a human network analysis server 5 that analyzes the human network between employees based on the positioning results of the positioning system 3. I have. The floor F includes four areas, a 101 conference room A1, a 102 conference room A2, a smoking room A3, and a cafeteria A4. At least one wireless LAN access point p1 to p4 is provided in each area A1 to A4. Is installed. The number of access points in each area is adjusted as appropriate.

  The positioning system 3 is a computer system that captures the location of each employee by measuring the position of the portable terminal held by each employee. Specifically, the positioning system 3 measures the position of the mobile terminal using a wireless LAN including the access points p1 to p4. Then, the positioning system 3 associates the identification information for identifying the portable terminal (employee) and the positioning time with the information indicating in which of the areas A1 to A4 the measured portable terminal exists, and the terminal position Information is periodically sent to the human network analysis server 5. Here, the identification information is stored in advance in each mobile terminal and can be collected via the access points p1 to p4. In this manner, the positioning system 3 detects the position of the mobile terminal held by the employee at each time, so that the human network analysis server 5 allows each employee in the floor F to select any of the areas A1 to A4 at each time. You can collect information about whether you were staying at.

  The human network server 5 includes a human network estimation unit 11 (relationship strength calculation unit), an information storage unit 13, a human network display unit 15, and an information conversion unit 19 (stay area detection unit). The information storage unit 13 includes a positioning result storage unit 21, a position attribute information storage unit 23 (area attribute storage unit), and a human network information storage unit 25.

  Among these, the position attribute information storage unit 23 of the information storage unit 13 stores an area attribute information table 23a indicating the area attributes set in the areas A1 to A4. In this human network analysis system 1, for each of the areas A1 to A4, the “business area (first area attribute)” indicating the area that the employee uses in the business, or the employee is a private business Any attribute of “non-work area (second area attribute)” indicating the area to be used is set. An example of the area attribute information table 23a is shown in FIG.

  The positioning result storage unit 21 of the information storage unit 13 periodically receives the terminal position information from the positioning system 3 described above via the information conversion unit 19. The information conversion unit 19 converts the terminal position information from the positioning system 3 into stay history information in which an employee ID for identifying an employee, a time, and an ID of a stay area where the employee stayed at the time are associated with each other. . Although not shown, the information conversion unit 19 stores a table in which an employee ID for identifying an employee is associated with identification information for the mobile terminal of the employee, and a table in which identification information for each access point is associated with an area ID. It is used for the process of converting the terminal position information into stay history information. The positioning result storage unit 21 accumulates the stay history information as needed and stores it as a stay history information table 21a. An example of the stay history information table 21a created here is shown in FIG.

  The human network estimation unit 11 performs a predetermined calculation based on the area attribute information table 23a and the stay history information table 21a. Then, the human network estimation unit 11 calculates “relationship strength” as an index indicating the intimacy of the relationship between employees traveling on the floor F, and stores it in the human network information storage unit 25 of the information storage unit 13. . Further, the human network display unit 15 graphicizes the structure of the human network formed by the employees based on the relationship strength between the employees stored in the human network information storage unit 25, and displays the screen on the monitor. To do. The human network display unit 15 can also display the structure of the human network on the monitor 27a of the client PC terminal 27 connected to the human network analysis server 5 via the network. It is possible to control permission / non-permission of display for each 27.

  Next, the hardware configuration of the human network analysis server 5 will be described. As shown in FIG. 3, the human network analysis server 5 includes a CPU 201 that executes an operating system, an application program, and the like, a main storage unit 202 that includes a ROM and a RAM, an auxiliary storage unit 203 that includes a hard disk, a network A communication control unit 204 such as a card, an input unit 205 such as a keyboard and a mouse, and an output unit 206 such as a monitor and a printer. Each function shown in FIG. 1 reads predetermined software on the CPU 201 and the main storage unit 202 shown in FIG. 2 and operates the communication control unit 204 under the control of the CPU 201, This is realized by reading and writing data in the storage unit 203.

  Next, an example of processing for analyzing and displaying a human network between employees on the floor F will be described based on the configuration of the human network analysis system 1 as described above. As shown in FIG. 4, this analysis / display process includes an area attribute setting process (S402), an employee position information collection process (S404), an employee grouping process (S406), and an inter-employee process. Including a process of calculating the relationship strength (S408) and a process of displaying a human network between employees (S410). Hereinafter, each process S402-S410 is each demonstrated in detail.

(Area attribute setting: S402)
First, the administrator of the human network analysis system 1 sets and inputs the area attributes of the areas A1 to A4 on the floor F by operating the input unit 205 (see FIG. 3) of the human network analysis server 5. An area attribute information table 23a as shown in FIG. 5 is created. Of the above-mentioned areas A1 to A4, 101 conference room A1 and 102 conference room A2 are classified into business areas used for business such as meetings and meetings, and smoking room A3 and cafeteria A4 are private outside business such as breaks. It is classified as a non-business area used for business.

  Therefore, based on the difference in the properties of the areas, the area attributes of the 101 meeting room A1 and the 102 meeting room A2 are set as “work area”, and the area attributes of the smoking room A3 and the cafeteria A4 are set as “non-work area”. Is set. The created area attribute information table 23 a is stored in the position attribute information storage unit 23. Note that this process S402 need only be performed when the area attribute settings of the areas A1 to A4 are changed, and does not have to be performed every time.

(Collecting employee location information: S404)
Next, the positioning system 3 (FIG. 1) measures the whereabouts of each employee who comes and goes on the floor F, and specifies in which area of the areas A1 to A4 each employee is staying. Here, a case where an employee is moved as shown in FIGS. 6A to 6C will be considered as an example. That is, in this example, on August 10, 2007, between 10:00 and 10:20, the employees Mr. Yoshida and Mr. Sato stay in the 101 meeting room A1 (FIG. 6 (a )). And from 12:00 to 12:20, Mr. Yoshida and Mr. Kominato stay in the cafeteria A4 (FIG. 6B). Furthermore, Mr. Tanaka, Mr. Yoshida, and Mr. Sato are staying in the 102 meeting room A2 from 13:00 to 13:20 (FIG. 6 (c)).

  The location of each employee is measured by the positioning system 3 as the position of each employee's mobile terminal, and the terminal position information is transmitted to the human network analysis server 5 at intervals of about once every 10 minutes, for example. Then, the stay history in which the employee ID, the area ID of the stay area, and the current time are associated with each other in the positioning result storage unit 21 (see FIG. 1) of the human network analysis server 5 via the information conversion unit 19. An information table 21a is stored. An example of such a stay history information table 21a is shown in FIG. Note that this processing S404 may be always automatically performed even when a special operation by the administrator of the human network analysis system 1 is not performed.

(Total of employees who are together: S406)
Subsequently, the human network estimation unit 11 (FIG. 1) counts the degree to which each group of employees stays in the same area at the same time based on the stay history information table 21a. Perform the process. In this process, when a certain employee group is staying in the same area at the same time, this employee group is assumed to be together. Hereinafter, this process will be described with reference to the flowchart of FIG.

  First, the human network estimation unit 11 refers to the stay history information table 21a (FIG. 7), and identifies employees staying at a certain time t in the area A1 (101 conference room) (S802). Next, it is determined whether or not two or more employees are staying in the area A1 within the time T0 retroactively from the time t (S804). If the determination in S804 is “Yes”, then the group of the above-mentioned employees staying in the area A1 together is at least T1 and is not the same as the employee already recorded. Is confirmed (S806). That is, only when a group of employees stays together in the same area for a time T1 or more is regarded as an aggregation target as if the employees were together. If “Yes” is determined in S806, a data record including the ID of the employee group, the time spent together, the area ID stayed together, and the last time stayed together is recorded ( S808). If the determination in S804 or S806 is “No”, the process proceeds to S810 without recording the data record.

  Next, the above processes S802 to S808 are sequentially performed in the same manner for all remaining areas A2 to A4, and similar data records are recorded (S810). Thereafter, by repeating the above-described processing S802 to S810 while changing the time t of further interest (S812), the same data record is recorded and accumulated. An example of the data record group 31 recorded and stored as described above is shown in FIG. Furthermore, the human network estimation unit 11 refers to the area attribute information table 23a (FIG. 5) of the position attribute information storage unit 23, and from the obtained data record group 31, the area attribute of the area where the user stays is “business area” “Is” and “out-of-business area” are extracted separately and re-aggregated as information for each employee group for each area attribute and tabulated. At this time, the number of times of being together, the total time of being together, and the time of being together last are derived for each group of employees by the aggregation processing of the data record group 31. An example of the aggregation table 33 created by such processing is shown in FIG.

  Here, the data of “business area” and the data of “non-work area” are aggregated separately, and the nature of intimacy between the employees varies depending on which area the employees contact. Because it is considered. In other words, the contact between employees in the “business area” is often a business meeting, for example, and the degree of contact between employees in the “work area” is determined by the degree of business intimacy between the employees. It is thought to reflect. In addition, contact between employees in the “non-work area” is often, for example, a conversation during a break, and the degree of contact between employees in the “non-work area” depends on the private It is thought to reflect the density.

  As shown in FIG. 10, according to the tabulation table 33 obtained by this tabulation, the number of times that the pair of Mr. Sato and Mr. Yoshida was together in the work area (101 meeting room or 102 meeting room) was two times. It is shown that the total time spent together was 50 minutes, and the last time spent together was 13:30 on August 10, 2007 (data number 1). In addition, Mr. Sato, Mr. Yoshida, and Mr. Tanaka have been together once in the work area (101 meeting room or 102 meeting room), and the total time spent together is 30 minutes. It is shown that the time of being together was 13:30 on August 10, 2007 (data number 2). In addition, Mr. Sato and Mr. Kominato were in the non-working area (smoking room or cafeteria) once, and the total time spent together was 20 minutes, the last time they were together Is 12:20 on August 10, 2007 (data number 3).

(Calculation of relationship strength between employees: S408)
Subsequently, the human network estimation unit 11 (FIG. 1) calculates “relationship strength” that is an index of closeness of each employee group based on the information shown in the aggregation table 33 of FIG. This relation strength RS is defined by the following mathematical formula.

The relationship strength RS (u1, u2) between employee u1 and employee u2 is
RS (u1, u2) = N (u1, u2) -ET (u1, u2) / Const1 (Formula F11)
The relationship strength RS (u1, u2, ..., un) of n people from employee u1 to employee un is
RS (u1, u2, ... un) = N (u1, u2, ... un) -ET (u1, u2, ... un) / Const1 (Formula F12)
However,
N (u1, u2): Number of times employee u1 and employee u2 were together (times)
ET (u1, u2): Number of days (days) since employee u1 and employee u2 were last together
N (u1, u2, ... un): Number of times employees u1-un were together (times)
ET (u1, u2, ... un): Number of days (days) from the last day when employees u1-un were together
Const1: Predetermined constant

Further, instead of the above formulas F11 and F12, the following formulas F21 and F22 may be employed.
The relationship strength RS (u1, u2) between employee u1 and employee u2 is
RS (u1, u2) = T (u1, u2) -ET (u1, u2) / Const2 (Formula F21)
The relationship strength RS (u1, u2, ..., un) of n people from employee u1 to employee un is
RS (u1, u2, ... un) = T (u1, u2, ... un) -ET (u1, u2, ... un) / Const2 (Formula F22)
However,
T (u1, u2): Total time (minutes) that employee u1 and employee u2 were together
T (u1, u2, ... un): Total time (minutes) that employees u1-un were together
Const2: Predetermined constant

  Here, the human network estimation unit 11 uses the above formula F11 based on the data (here, data numbers 1 and 2) related to the “business area” attribute among the information shown in FIG. Find the relationship strength for the “business area”. The strength of the relationship obtained in this way is derived from information that aggregates only the contacts in the work area between employees. For example, it is related to work such as whether or not people often work together. This seems to indicate the intimacy among employees. An example of the relationship strength obtained in this way is shown in FIG.

  Similarly, the human network estimation unit 11 uses the above formula F11 based on the data related to the “non-business area” attribute (here, data number 3) in the information shown in FIG. Find the strength of the relationship for “out-of-business area”. Since the strength of the relationship thus obtained is derived from the information obtained by counting only the contacts in the non-work area between employees, for example, whether or not there is often a break in the smoking room together, This seems to indicate the private intimacy among employees. An example of the relationship strength obtained in this way is shown in FIG.

  Further, in calculating the relationship strength, the same tendency can be obtained with respect to the magnitude relationship of the relationship strength of each employee group by using Formula F21 instead of Formula F11. FIG. 12A shows an example of the relationship strength related to the “work area”, and FIG. 12B shows an example of the relationship strength related to the “non-work area” when Expression F21 is used. In Formula F11 or Formula F21, the number of times or the total time in which the same area was simultaneously used for calculating the relationship strength is used, which is referred to as the degree of coincidence of the stay areas. However, the degree of coincidence of the stay areas is not limited to the above, and may be, for example, a combination of the above-mentioned number of times and the total time, or any other reasonable measure. Further, Formula F12 or Formula F22 may be used to include the relationship strength of a group of three or more employees. FIG. 13A shows an example of the relationship strength related to the “work area”, and FIG. 13B shows an example of the relationship strength related to the “non-work area” when Expression F12 is used. Further, in the case of using Formula F22, an example of the relationship strength relating to “work area” is shown in FIG. 14A, and an example of the relationship strength relating to “non-work area” is shown in FIG.

  As described above, the human network estimation unit 11 independently calculates the relationship strength in the “working area” between employees and the relationship strength in the “non-working area” independently. Therefore, in this human network analysis system 1, a public human network formed by business relationships between employees is separated from a private human network formed by private relationships outside the business. I can grasp it.

(Process for displaying a human network between employees: S410)
Next, the human network display unit 15 (FIG. 1) graphicizes the structure of the human network formed between the employees based on the relationship strength between the employees obtained in S408, and outputs an output unit. A screen is displayed on the monitor 206 (FIG. 3) or the monitor 27 (FIG. 1) of the PC terminal 27. In the following, description will be made based on the relational strength shown in FIGS.

  As shown in FIG. 15A, the human network display unit 15 refers to the relationship strength in FIG. Mr. Yoshida and Mr. Tanaka who have relationship strength in the area are listed on the screen. In this case, they are listed in descending order starting from the largest relationship with Mr. Sato. That is, here, the relationship strength between Mr. Sato and Mr. Yoshida is 2, and the relationship strength between Mr. Sato and Mr. Tanaka is 1, so Mr. Yoshida is displayed above. Such a display method of order of relationship strength makes it easier to visually understand the intimacy of business among employees. At this time, the profiles of Mr. Yoshida and Mr. Tanaka listed may be displayed together on the screen.

  Since such screen displays represent business relationships between employees, there are few privacy issues even if they are disclosed to all employees. Rather, they are disclosed and shared information to all employees. This will contribute to the promotion of business collaboration among employees. Therefore, such a display of the personal relationship on the job is, for example, displayed on a shared PC terminal that can be referred to by all employees among the PC terminals 27 (FIG. 1) connected to the human network analysis server 5. May be performed.

  On the other hand, as shown in FIG. 15B, when displaying the personal relationship of Mr. Sato, the human network display unit 15 refers to the relationship strength of FIG. In the screen, Mr. Ogura who has a relationship strength in the non-business area is displayed on the screen. Since such a screen display represents a private personal relationship between employees, it is necessary to consider privacy issues. Therefore, such a screen display can be displayed only on the personal PC terminal of the employee himself / herself related to the display or the personal PC terminal of the employee permitted to the employee related to the display among the PC terminals 27 (FIG. 1). You may go.

  As described above, according to the system 1, the process by the human network estimation unit 11 is formed by a public human network formed by a business relationship between employees and a private relationship outside the business. A private human network is analyzed separately. Therefore, according to this human network analysis system 1, while limiting the disclosure of a private human network from the viewpoint of privacy, the public human network for business purposes is the purpose of promoting business collaboration between employees. This makes it possible to operate such as opening to all employees.

  As a display method for visually displaying the human network structure between employees, for example, a screen display as shown in FIGS. 16A and 16B may be considered. For example, in FIG. 16A, Mr. Yoshida and Mr. Tanaka who have a relationship strength in the business area with Mr. Sato are displayed on the screen as character strings “Yoshida” and “Tanaka”. In this case, the greater the strength of the relationship with Mr. Sato, the closer it is displayed to the character string “Sato”, so even with such a display method, it becomes easier to visually understand the intimacy between employees. . FIG. 16B is an example of a screen that visually shows the relationship strength in the “non-business area” with the same display method.

  Further, as another display method for visually displaying the human network structure between employees, for example, a screen display as shown in FIGS. 17A, 17B, and 17C can be considered. For example, in FIG. 17A, Mr. Yoshida and Mr. Tanaka who have a relationship strength with Mr. Sato in the work area are displayed on the screen as character strings “Yoshida” and “Tanaka”. In this case, multiple ellipses surrounding the character string “Sato” in the center are displayed, and the relationship strength value is associated with the position of the ellipse. And the employee whose relationship strength with Mr. Sato is high is included in the inner ellipse and displayed. Such a display method also makes it easier to visually understand the intimacy of business among employees. FIG. 17B is an example of a screen that visually shows the relationship strength in the “non-business area” with the same display method.

  In addition, when this display method is adopted, when a large number of ellipses are displayed, the display may be difficult to understand. In order to avoid this, the ellipses to be displayed may be narrowed down as follows. That is, when displaying the ellipse G1 corresponding to the relationship strength RS1 and the ellipse G2 corresponding to the relationship strength RS2 to be displayed outside thereof, the difference between the relationship strength RS1 and the relationship strength RS2 is a predetermined value. When it is less than the threshold, the display of the ellipse G1 is omitted. In the screen display when such processing is performed on the screen of FIG. 17A, the display of the inner ellipse G1 is omitted as shown in FIG.

  The present invention is not limited to the embodiment described above. For example, the positioning system 3 of the human network analysis system 1 uses a WLAN access point to identify the position of the user. Instead, for example, a mobile phone equipped with a wireless LAN function is used. Adopting a method that uses the difference in arrival time of wireless LAN radio waves transmitted from the mobile phone, a method that uses the strength of radio waves from the access point, or a method that installs a dedicated WLAN positioning device in each area You may do it. Further, instead of the positioning system 3, a positioning system using any one of sensors such as Bluetooth, infrared sensor, ultrasonic sensor, RFID, or a combination of a plurality of these sensors may be adopted. A positioning system using a mobile phone base station may be adopted, or a positioning system using a GPS system may be adopted.

It is a block diagram showing one embodiment of a human network analysis system concerning the present invention. FIG. 2 is a plan view of a company floor to which the human network analysis system of FIG. 1 is applied. It is a block diagram which shows the hardware constitutions of the human network analysis server contained in the system of FIG. It is a flowchart which shows the human network analysis and display process by the system of FIG. It is a figure which shows the area attribute information table used with the system of FIG. (A)-(c) is a top view which shows the position and time of the employee in the floor of FIG. 2, respectively. It is a figure which shows the stay history information table produced by the process by the system of FIG. It is a flowchart which shows the process performed in the human network estimation part of the system of FIG. It is a figure which shows the data record group produced by the process by the system of FIG. It is a figure which shows the total table created by the process by the system of FIG. (A) is a figure which shows the relationship strength in the business area between employees, (b) is a figure which shows the relationship strength in the non-business area between employees. (A) is a figure which shows the relationship strength in the business area between employees, (b) is a figure which shows the relationship strength in the non-business area between employees. (A) is a figure which shows the relationship strength in the business area between employees, (b) is a figure which shows the relationship strength in the non-business area between employees. (A) is a figure which shows the relationship strength in the business area between employees, (b) is a figure which shows the relationship strength in the non-business area between employees. (A) is a screen display showing the personal relationship regarding the business between employees, and (b) is a screen display showing the personal relationship regarding the outside business between employees. (A) is a screen display showing the personal relationship regarding the business between employees, and (b) is a screen display showing the personal relationship regarding the outside business between employees. (A), (c) is a screen display which shows the personal relationship regarding the business between employees, (b) is a screen display which shows the personal relationship regarding the outside business between employees.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Human network analysis system, 3 ... Positioning system (stay area detection means), 5 ... Human network analysis server, 11 ... Human network estimation part (relation strength calculation means), 15 ... Human network display part (human Network display means), 19 ... information conversion section (stay area detection means), 23 ... location attribute information storage section (area attribute information storage means), 23a ... area attribute information table, 27a ... PC terminal monitor (human network) Display means), 206 ... output section (human network display means), A1 ... 101 meeting room (business area), A2 ... 102 meeting room (working area), A3 ... smoking room (non-working area), A4 ... cafeteria ( Outside business area), F ... Floor (predetermined area).

Claims (8)

In a human network analysis system for analyzing a human network formed between users who come and go within a predetermined area,
Area attribute information storage means for storing area attribute information indicating an area attribute of each area included in the predetermined area;
A stay area detecting means for detecting a stay area that is an area including the location of each of the users based on the position of each of the users measured in the predetermined area;
Based on the degree and the area attribute information stay area obtained by the stay area detecting means matches between each said user, have a, a relationship intensity calculating means for calculating the relationship strength between the user,
The relationship strength calculating means includes
With reference to the area attribute information of the area attribute information storage means, based on the area attribute of the stay area matched between the users, the relationship strength for each area attribute is calculated,
In the predetermined area, a business area having a first area attribute and set as an area used for business, and a business area having a second area attribute and used as a private business Area, and
The relationship strength calculating means includes
Based on the degree to which the stay areas at the same time match among the plurality of users, and the matching stay areas have the first area attribute, the human relational strength of business between the users To calculate
Based on the degree to which the stay areas at the same time coincide with each other among the plurality of users, and the matching stay areas have the second area attribute, the human relationship strength outside the business between the users Human network analysis system characterized by calculating The relationship strength calculating means includes
Accumulating stay history information associating each user with the time and the stay area of the user at the time obtained by the stay area detection unit;
2. The person according to claim 1 , wherein, based on the stay history information, the relationship strength between the users is calculated according to a degree to which a plurality of users stay in the same area at the same time. Network analysis system. The stay area detection means includes:
Human network analysis system according to claim 1 or 2 mobile information terminal areas exist, and detecting as a stay area of the user of each said user holds. Network display means for displaying a human network formed between the users in an area having a predetermined area attribute based on the strength of personal relation between the users obtained by the relation strength calculation means. further human network analysis system according to any one of claims 1 to 3, characterized in that with. The relationship strength calculating means includes
When N is the number of times the plurality of users have been together, and ET is the elapsed time since the last time the plurality of users were together,
The relationship strength RS between the users is
RS = N-ET / constant
5. The human network analysis system according to claim 1, wherein the human network analysis system is calculated based on the mathematical formula: The relationship strength calculating means includes
When the total time that the plurality of users were together is T, and the elapsed time from the last time the plurality of users were together is ET,
The relationship strength RS between the users is
RS = T-ET / constant
5. The human network analysis system according to claim 1, wherein the human network analysis system is calculated based on the mathematical formula: In a human network analysis server that analyzes a human network formed between users who come and go within a predetermined area,
Area attribute information storage means for storing area attribute information indicating an area attribute of each area included in the predetermined area;
A stay area detecting means for detecting a stay area that is an area including the location of each of the users based on the position of each of the users measured in the predetermined area;
A relationship strength calculating means for calculating a relationship strength between the users based on the degree to which the stay areas obtained by the stay area detecting means match between the users and the area attribute;
Have
The relationship strength calculating means includes
With reference to the area attribute information of the area attribute information storage means, based on the area attribute of the stay area matched between the users, the relationship strength for each area attribute is calculated,
In the predetermined area, a business area having a first area attribute and set as an area used for business, and a business area having a second area attribute and used as a private business Area, and
The relationship strength calculating means includes
Based on the degree to which the stay areas at the same time match among the plurality of users, and the matching stay areas have the first area attribute, the human relational strength of business between the users To calculate
Based on the degree to which the stay areas at the same time coincide with each other among the plurality of users, and the matching stay areas have the second area attribute, the human relationship strength outside the business between the users A human network analysis server characterized by calculating In a human network analysis method for analyzing a human network formed between users who come and go within a predetermined area,
An area attribute information storage step of storing area attribute information indicating an area attribute of each area included in the predetermined area in an area attribute information storage means;
A stay area detecting step, wherein the stay area detecting means detects a stay area that is an area including the location of each user based on the position of each user measured in the predetermined area;
A relationship strength calculating step for calculating a relationship strength between the users based on the degree of matching of the stay areas obtained in the stay area detection step between the users and the area attribute; Have
The relationship strength calculating means includes
With reference to the area attribute information of the area attribute information storage means, based on the area attribute of the stay area matched between the users, the relationship strength for each area attribute is calculated,
In the predetermined area, a business area having a first area attribute and set as an area used for business, and a business area having a second area attribute and used as a private business Area, and
The relationship strength calculating means includes
Based on the degree to which the stay areas at the same time match among the plurality of users, and the matching stay areas have the first area attribute, the human relational strength of business between the users To calculate
Based on the degree to which the stay areas at the same time coincide with each other among the plurality of users, and the matching stay areas have the second area attribute, the human relationship strength outside the business between the users The human network analysis method characterized by calculating .

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