CN112487257B - Office personnel relationship analysis method - Google Patents
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Abstract
The invention provides an office personnel relationship analysis method, which is used for monitoring the contact activity of office personnel, constructing a personnel contact relationship graph database, analyzing working daily reports and extracting personnel item relationships, and constructing a personnel item graph database; based on a personnel contact relation graph database, calculating the personnel contact, the contacted degree and the contact relation degree between every two personnel, and detecting the personnel contact group; based on the personnel item map database, calculating item correlation degree between every two personnel; based on the calculation result, the degree of deviation of the degree of contact between the persons from the degree of relation to the matter is calculated. The office personnel relationship analysis method provided by the invention analyzes the personnel contact relationship, the actual activities of the personnel and the relativity of the matters responsible or participated by the personnel, provides data-level support for monitoring abnormal contact relationship and improving working efficiency, and realizes comprehensive and objective evaluation of personnel value.
Description
Technical Field
The invention relates to the technical field of personnel relationship analysis, in particular to an office personnel relationship analysis method.
Background
In an office, people are contacted with each other every day, wherein some of the contacts are effective contacts and some of the contacts are ineffective contacts, and from the contact relation of office people and the personnel item relation in working daily reports, the contact relation degree of the analysis personnel with or by other people, the contact relation degree of the personnel between every two people, the item correlation degree of the personnel between every two people and the personnel contact group detection are used for providing support of a plurality of data layers for working evaluation, abnormal contact relation detection and improvement of the effectiveness of the work of the office personnel.
Disclosure of Invention
The invention aims to provide an office personnel relationship analysis method, which analyzes personnel contact relationship, actual activities of personnel and relativity of matters responsible or participated by the personnel, provides data-level support for monitoring abnormal contact relationship and improving working efficiency, and realizes comprehensive and objective evaluation of personnel value.
In order to achieve the above object, the present invention provides the following solutions:
an office personnel relationship analysis method comprises the following steps:
step 1, analyzing a personnel contact relation, and establishing a personnel contact relation map database:
monitoring the contact relation and the contact time between the personnel and recording the contact relation and the contact time into a personnel contact relation map database; calculating the contacted degree of each person based on the person contact relation map database, ranking the persons according to the contacted degree from high to low, calculating the contact degree of each person, and ranking the persons according to the contact degree from high to low; calculating the contact relation degree between every two persons, ranking the contact relation between each person and other persons according to the contact relation degree from high to low, and detecting the contact group of the persons according to the contact relation degree between every two persons;
step 2, analyzing personnel event relationship, and establishing a personnel event map database:
analyzing working daily reports, extracting personnel item relations and item keyword relations, and recording the personnel item relations and the item keyword relations into a personnel item relation map database; calculating the importance degree of each item and the item participation degree of each person according to the item relation graph database, ranking the persons according to the item participation degree, calculating the item correlation degree between every two persons, and ranking the item correlation relation between the person and other persons according to the item correlation degree from high to low;
step 3, carrying out deviation analysis on the personnel contact relationship and the personnel item relationship:
collecting the contacted degree and ranking of each person, the contacted degree and ranking, the item participation degree and ranking, calculating the deviation of the contacted degree ranking and the item participation degree ranking, and calculating the deviation of the contacted degree ranking and the item participation degree ranking; and collecting the contact relation degree and the rank of each person and other persons, the item correlation degree and the rank, and calculating the deviation of the contact relation rank and the item correlation degree rank.
Optionally, in step 1, the contact relationship and the contact duration between the personnel are monitored and recorded in a personnel contact relationship map database, specifically: and monitoring contact activities among the personnel from a computer vision identity recognition system, a conference record and an online office chat record, calculating to obtain a contact person, a contacted person and contact time, and storing the contact person, the contacted person and the contact time into a personnel contact relation map database.
Optionally, in step 1, the step of calculating the contacted degree of each person, and ranking the persons according to the contacted degree from high to low specifically includes:
calculating the contacted PR_P value of each person according to a person contact relation graph database by using a PageRank algorithm, wherein PR_P (i) represents the contacted PR_P value of the ith person, the summation of the contacted time length of each person is denoted as TP_P, the contacted time length of the ith person is denoted as TP_P (i), the contacted degree WP_P of each person is calculated, wherein WP_P (i) represents the contacted degree of the ith person, and the calculation formula is as follows:
WP_P(i)＝PR_P(i)*TP_P(i)
the person ranks from high to low according to the wp_p value, and the wp_p value rank of the i-th person is represented by rp_p (i).
Optionally, in step 1, the step of calculating the contact degree of each person and ranking the persons from high to low according to the contact degree specifically includes:
reversing the pointing direction in the personnel contact relation map database, pointing to a contacted person by the contacted person, and calculating a contact PR_A value of each person by using a PageRank algorithm, wherein PR_A (i) represents the PR_A value of the ith person contacting other persons; summing the time periods of each person contacting other people to be called TP_A, wherein TP_A (i) represents the time period of the ith person contacting the other people, and calculating the contact degree WP_A of each person, wherein WP_A (i) represents the contact degree of the ith person, and the calculation formula is as follows:
WP_A(i)＝PR_A(i)*TP_A(i)
the person ranks from high to low according to the WP_A value, and the WP_A value rank of the ith person is denoted by RP_A (i).
Optionally, in step 1, the degree of contact relation between each two persons is calculated, and the contact relation between each person and other persons is ranked according to the degree of contact relation from high to low, which specifically includes:
summarizing the mutual contact time length between every two persons as the contact relation degree, wherein the contact relation degree between the ith person and the jth person is named as WP_R (i, j), ranking the contact relation between each person and other persons according to the WP_R value from high to low, and using RP_R (i, j) to represent the ranking of the jth person in the contact relation of the ith person.
Optionally, in step 1, the person contact group is detected according to the contact relationship degree between every two persons, specifically:
establishing an oscillography of each person, adding each person into the oscillography of the person, adding the top N-1 persons in the closest contact relationship with the person into the oscillography of the person according to the contact relationship degree WP_R value and the ranking RP_R value, wherein N represents the maximum number of the oscillography, and obtaining a person contact group according to the oscillography of each person by using a frequent item mining algorithm.
Optionally, in step 2, the working daily report is analyzed, the personnel item relationship and the item keyword relationship are extracted, and recorded into a personnel item relationship map database, specifically:
collecting matters filled in the working daily report, the duration of each matter and specific working contents, and extracting keywords from all the working contents of each matter to obtain the relationship between the keywords and the matters; summarizing the working time of each person participating in each item to obtain the relation among the person, the item and the working time; and storing the keyword, the item relation and the personnel, the item and the working time length relation into a personnel item map database.
Optionally, in step 2, the calculating the importance degree of each item specifically includes:
according to the personnel item map database, the PR_S value of each item is calculated by using the PageRank algorithm, and the importance PR_S value of the ith item is represented by PR_S (i).
Optionally, in step 2, the calculating the participation degree of each person specifically includes:
multiplying the importance PR_S value of each item participated by each person by the time of participated item, and summing all the products to obtain the item participated degree WP_S value of each person, wherein the calculation formula is as follows:
WP_S(i)＝SUM j (TP_S(i,j)*PR_S(j))
wherein wp_s (i) represents the item participation degree of the ith person, tp_s (i, j) represents the time period of participation of the ith person in the jth item, pr_s (j) represents the importance degree of the jth item, the persons are ranked from high to low according to the item participation degree wp_s value, and rp_s (i) represents the item participation degree ranking of the ith person.
Optionally, in step 2, the calculating the item correlation degree between every two people specifically includes:
finding out matters which two persons participate in together, and calculating the relation degree WP_SR value of the matters between the two persons, wherein the calculation formula is as follows:
WP_SR(i,k)＝SUM j (TP_S(i,j)*PR_S(j)*TP_S(k,j))
wherein wp_sr (i, k) represents the degree to which the ith person is related to the item of the kth person, pr_s (j) represents the degree of importance of the jth item, tp_s (i, j) represents the length of time for which the ith person participates in the jth item, tp_s (k, j) represents the length of time for which the kth person participates in the jth item;
ranking the item correlations of each person with other persons from high to low by the item correlation wp_sr value, the rank of the jth person in the item correlations of the ith person is denoted rp_sr (i, j).
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the office personnel relationship analysis method provided by the invention, the personnel contact relationship graph database is constructed by monitoring the contact activity of office personnel, the contact or contacted degree of the personnel and the contact relationship degree between every two of the personnel can be calculated, the personnel item graph database is constructed by analyzing the daily report of work to extract the item relationship of the personnel, the item correlation degree between every two of the personnel can be calculated, the deviation degree of the contact degree between the personnel and the item correlation degree can be calculated according to the calculation result, and a plurality of data level supports can be provided for the work evaluation and abnormal contact relationship monitoring of the office personnel and the improvement of the work efficiency; the personnel contact relation graph database and the personnel item contact relation graph database are constructed, and various relations can be directly obtained from the graph, so that the method is simple and clear; all the degree indexes obtained through calculation are ranked, and the influence of all the degree indexes can be intuitively observed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a general flow chart of an office personnel relationship analysis method according to an embodiment of the present invention;
FIG. 2 is an exemplary graph of a human contact relationship map;
FIG. 3 is an illustration of an example personnel event map;
FIG. 4 is a flow chart of a constructor contact relationship map;
FIG. 5 is a constructor event atlas flow chart.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide an office personnel relationship analysis method, which analyzes personnel contact relationship, actual activities of personnel and relativity of matters responsible or participated by the personnel, provides data-level support for monitoring abnormal contact relationship and improving working efficiency, and realizes comprehensive and objective evaluation of personnel value.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1 to 5, the method for analyzing the relationship between office personnel provided by the embodiment of the invention comprises the following steps:
step 1, analyzing a personnel contact relation, and establishing a personnel contact relation map database:
monitoring the contact relation and the contact time between the personnel and recording the contact relation and the contact time into a personnel contact relation map database; calculating the contacted degree of each person based on the person contact relation map database, ranking the persons according to the contacted degree from high to low, calculating the contact degree of each person, and ranking the persons according to the contact degree from high to low; calculating the contact relation degree between every two persons, ranking the contact relation between each person and other persons according to the contact relation degree from high to low, and detecting the contact group of the persons according to the contact relation degree between every two persons;
step 2, analyzing personnel event relationship, and establishing a personnel event map database:
analyzing working daily reports, extracting personnel item relations and item keyword relations, and recording the personnel item relations and the item keyword relations into a personnel item relation map database; calculating the importance degree of each item and the item participation degree of each person according to the item relation graph database, ranking the persons according to the item participation degree, calculating the item correlation degree between every two persons, and ranking the item correlation relation between the person and other persons according to the item correlation degree from high to low;
step 3, carrying out deviation analysis on the personnel contact relationship and the personnel item relationship:
collecting the contacted degree and ranking of each person, the contacted degree and ranking, the item participation degree and ranking, calculating the deviation of the contacted degree ranking and the item participation degree ranking, and calculating the deviation of the contacted degree ranking and the item participation degree ranking; and collecting the contact relation degree and the rank of each person and other persons, the item correlation degree and the rank, and calculating the deviation of the contact relation rank and the item correlation degree rank.
In step 1, the contact relation and the contact duration between the personnel are monitored and recorded in a personnel contact relation map database, specifically: and monitoring contact activities among the personnel from a computer vision identity recognition system, a conference record and an online office chat record, calculating to obtain a contact person, a contacted person and contact time, and storing the contact person, the contacted person and the contact time into a personnel contact relation map database.
As shown in fig. 4, the specific flow of the constructor contact relation map is as follows: monitoring contact activities among the personnel by using a computer vision identity recognition system, recognizing a contacted person according to the station information of the personnel, and if the contacted person cannot be recognized, each personnel in the contact activities is both the contacted person and the contacted person; for each conference, recording participants and conference duration, wherein each participant is a contacted person and a contacted person as one contact activity; according to the chat record of the online office software, monitoring online contact activity among people, if two people chat, the initiator of the chat is a contactor, and if a plurality of people chat, each person is a contacted person and a contacted person; and recording all contactors, contactors and contact time lengths, summing the contact time lengths of each pair of contactors and contactors, obtaining (contactor, contactor and total contact time length) and storing the obtained (contactor, contactor and total contact time length) into a personnel contact relation graph database, wherein fig. 2 is a personnel contact relation graph of 5 persons.
In step 1, the contacted degree of each person is calculated, and the person is ranked according to the contacted degree from high to low, specifically:
calculating the contacted PR_P value of each person according to a person contact relation graph database by using a PageRank algorithm, wherein PR_P (i) represents the contacted PR_P value of the ith person, the summation of the contacted time length of each person is denoted as TP_P, the contacted time length of the ith person is denoted as TP_P (i), the contacted degree WP_P of each person is calculated, wherein WP_P (i) represents the contacted degree of the ith person, and the calculation formula is as follows:
WP_P(i)＝PR_P(i)*TP_P(i)
the person ranks from high to low according to the wp_p value, and the wp_p value rank of the i-th person is represented by rp_p (i).
In step 1, the contact degree of each person is calculated, and the person is ranked according to the contact degree from high to low, specifically:
reversing the pointing direction in the personnel contact relation map database, pointing to a contacted person by the contacted person, and calculating a contact PR_A value of each person by using a PageRank algorithm, wherein PR_A (i) represents the PR_A value of the ith person contacting other persons; summing the time periods of each person contacting other people to be called TP_A, wherein TP_A (i) represents the time period of the ith person contacting the other people, and calculating the contact degree WP_A of each person, wherein WP_A (i) represents the contact degree of the ith person, and the calculation formula is as follows:
WP_A(i)＝PR_A(i)*TP_A(i)
the person ranks from high to low according to the WP_A value, and the WP_A value rank of the ith person is denoted by RP_A (i).
In step 1, the degree of contact relation between every two people is calculated, and the contact relation between each person and other people is ranked according to the degree of contact relation from high to low, specifically:
summarizing the mutual contact time length between every two persons as the contact relation degree, wherein the contact relation degree between the ith person and the jth person is named as WP_R (i, j), ranking the contact relation between each person and other persons according to the WP_R value from high to low, and using RP_R (i, j) to represent the ranking of the jth person in the contact relation of the ith person.
In step 1, the person contact group is detected through the contact relation degree between every two persons, specifically:
establishing an oscillography of each person, adding each person into the oscillography of the person, adding the top N-1 persons in the closest contact relationship with the person into the oscillography of the person according to the contact relationship degree WP_R value and the ranking RP_R value, wherein N represents the maximum number of the oscillography, and obtaining a person contact group according to the oscillography of each person by using a frequent item mining algorithm.
In step 2, the working daily report is analyzed, the personnel item relation and the item keyword relation are extracted and recorded into a personnel item relation map database, specifically:
collecting matters filled in the working daily report, the duration of each matter and specific working contents, and extracting keywords from all the working contents of each matter to obtain the relationship between the keywords and the matters; summarizing the working time of each person participating in each item to obtain the relation among the person, the item and the working time; and storing the keyword, the item relation and the personnel, the item and the working time length relation into a personnel item map database.
As shown in fig. 5, the specific flow of the constructor item relation map is as follows: analyzing the daily report of work to obtain matters, the time length of each matters and specific work content, extracting keywords from all work content of each matters to obtain (keywords, matters) relations, summarizing the work time length of each matters participated by each person to obtain (personnel, matters and work time length) relations, and storing the (keywords, matters) relations and the (personnel, matters and work time length) relations into a personnel matters relation map database, for example, a personnel matters relation map shown in fig. 3 comprises 5 personnel, 3 times and 7 extracted keywords.
In step 2, the calculating the importance degree of each item specifically includes:
according to the personnel item map database, the PR_S value of each item is calculated by using the PageRank algorithm, and the importance PR_S value of the ith item is represented by PR_S (i).
In step 2, the calculating the participation degree of each person specifically includes:
multiplying the importance PR_S value of each item participated by each person by the time of participated item, and summing all the products to obtain the item participated degree WP_S value of each person, wherein the calculation formula is as follows:
WP_S(i)＝SUM j (TP_S(i,j)*PR_S(j))
wherein wp_s (i) represents the item participation degree of the ith person, tp_s (i, j) represents the time period of participation of the ith person in the jth item, pr_s (j) represents the importance degree of the jth item, the persons are ranked from high to low according to the item participation degree wp_s value, and rp_s (i) represents the item participation degree ranking of the ith person.
In step 2, the degree of item correlation between every two of the staff is specifically:
finding out matters which two persons participate in together, and calculating the relation degree WP_SR value of the matters between the two persons, wherein the calculation formula is as follows:
WP_SR(i,k)＝SUM j (TP_S(i,j)*PR_S(j)*TP_S(k,j))
wherein wp_sr (i, k) represents the degree to which the ith person is related to the item of the kth person, pr_s (j) represents the degree of importance of the jth item, tp_s (i, j) represents the length of time for which the ith person participates in the jth item, tp_s (k, j) represents the length of time for which the kth person participates in the jth item;
ranking the item correlations of each person with other persons from high to low by the item correlation wp_sr value, the rank of the jth person in the item correlations of the ith person is denoted rp_sr (i, j).
According to the office personnel relationship analysis method provided by the invention, the personnel contact relationship graph database is constructed by monitoring the contact activity of office personnel, the contact or contacted degree of the personnel and the contact relationship degree between every two of the personnel can be calculated, the personnel item graph database is constructed by analyzing the daily report of work to extract the item relationship of the personnel, the item correlation degree between every two of the personnel can be calculated, the deviation degree of the contact degree between the personnel and the item correlation degree can be calculated according to the calculation result, and a plurality of data level supports can be provided for the work evaluation and abnormal contact relationship monitoring of the office personnel and the improvement of the work efficiency; the personnel contact relation graph database and the personnel item contact relation graph database are constructed, and various relations can be directly obtained from the graph, so that the method is simple and clear; all the degree indexes obtained through calculation are ranked, and the influence of all the degree indexes can be intuitively observed.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. An office personnel relationship analysis method is characterized by comprising the following steps:
step 1, analyzing a personnel contact relation, and establishing a personnel contact relation map database:
monitoring the contact relation and the contact time between the personnel and recording the contact relation and the contact time into a personnel contact relation map database; calculating the contacted degree of each person based on the person contact relation map database, ranking the persons according to the contacted degree from high to low, calculating the contact degree of each person, and ranking the persons according to the contact degree from high to low; calculating the contact relation degree between every two persons, ranking the contact relation between each person and other persons according to the contact relation degree from high to low, and detecting the contact group of the persons according to the contact relation degree between every two persons;
step 2, analyzing personnel event relationship, and establishing a personnel event map database:
analyzing working daily reports, extracting personnel item relations and item keyword relations, and recording the personnel item relations and the item keyword relations into a personnel item relation map database; calculating the importance degree of each item and the item participation degree of each person according to the item relation graph database, ranking the persons according to the item participation degree, calculating the item correlation degree between every two persons, and ranking the item correlation relation between the person and other persons according to the item correlation degree from high to low;
step 3, carrying out deviation analysis on the personnel contact relationship and the personnel item relationship:
collecting the contacted degree and ranking of each person, the contacted degree and ranking, the item participation degree and ranking, calculating the deviation of the contacted degree ranking and the item participation degree ranking, and calculating the deviation of the contacted degree ranking and the item participation degree ranking; and collecting the contact relation degree and the rank of each person and other persons, the item correlation degree and the rank, and calculating the deviation of the contact relation rank and the item correlation degree rank.
2. The method for analyzing the relationship between staff in the office according to claim 1, wherein in step 1, the contact relationship and the contact duration between the staff are monitored and recorded in a staff contact relationship map database, specifically: and monitoring contact activities among the personnel from a computer vision identity recognition system, a conference record and an online office chat record, calculating to obtain a contact person, a contacted person and contact time, and storing the contact person, the contacted person and the contact time into a personnel contact relation map database.
3. The method for analyzing the relationship between people in offices according to claim 1, wherein in step 1, the degree of contact of each person is calculated, and the people are ranked according to the degree of contact from high to low, specifically:
calculating the contacted PR_P value of each person according to a person contact relation graph database by using a PageRank algorithm, wherein PR_P (i) represents the contacted PR_P value of the ith person, the summation of the contacted time length of each person is denoted as TP_P, the contacted time length of the ith person is denoted as TP_P (i), the contacted degree WP_P of each person is calculated, wherein WP_P (i) represents the contacted degree of the ith person, and the calculation formula is as follows:
WP_P(i)＝PR_P(i)*TP_P(i)
the person ranks from high to low according to the wp_p value, and the wp_p value rank of the i-th person is represented by rp_p (i).
4. The method for analyzing the relationship between people in offices according to claim 3, wherein in step 1, the contact degree of each person is calculated, and the people are ranked according to the contact degree from high to low, specifically:
reversing the pointing direction in the personnel contact relation map database, pointing to a contacted person by the contacted person, and calculating a contact PR_A value of each person by using a PageRank algorithm, wherein PR_A (i) represents the PR_A value of the ith person contacting other persons; summing the time periods of each person contacting other people to be called TP_A, wherein TP_A (i) represents the time period of the ith person contacting the other people, and calculating the contact degree WP_A of each person, wherein WP_A (i) represents the contact degree of the ith person, and the calculation formula is as follows:
WP_A(i)＝PR_A(i)*TP_A(i)
the person ranks from high to low according to the WP_A value, and the WP_A value rank of the ith person is denoted by RP_A (i).
5. The method for analyzing the relationship between people in an office according to claim 1, wherein in step 1, the degree of contact relationship between each two people is calculated, and the contact relationship between each person and other people is ranked according to the degree of contact relationship from high to low, specifically:
summarizing the mutual contact time length between every two persons as the contact relation degree, wherein the contact relation degree between the ith person and the jth person is named as WP_R (i, j), ranking the contact relation between each person and other persons according to the WP_R value from high to low, and using RP_R (i, j) to represent the ranking of the jth person in the contact relation of the ith person.
6. The method for analyzing the relationship between people in an office according to claim 5, wherein in step 1, the contact group of people is detected by the contact relationship degree between people, specifically:
establishing an oscillography of each person, adding each person into the oscillography of the person, adding the top N-1 persons in the closest contact relationship with the person into the oscillography of the person according to the contact relationship degree WP_R value and the ranking RP_R value, wherein N represents the maximum number of the oscillography, and obtaining a person contact group according to the oscillography of each person by using a frequent item mining algorithm.
7. The method for analyzing the relationship between staff in the office according to claim 1, wherein in the step 2, the working daily report is analyzed, the relationship between staff item and item keyword is extracted, and the relationship is recorded in a staff item relationship map database, specifically:
collecting matters filled in the working daily report, the duration of each matter and specific working contents, and extracting keywords from all the working contents of each matter to obtain the relationship between the keywords and the matters; summarizing the working time of each person participating in each item to obtain the relation among the person, the item and the working time; and storing the keyword, the item relation and the personnel, the item and the working time length relation into a personnel item map database.
8. The office personnel relationship analysis method according to claim 7, wherein in step 2, the calculating the importance degree of each item is specifically:
according to the personnel item map database, the PR_S value of each item is calculated by using the PageRank algorithm, and the importance PR_S value of the ith item is represented by PR_S (i).
9. The method for analyzing the relationship between office staff as claimed in claim 8, wherein in step 2, the calculating the participation degree of each staff is specifically:
multiplying the importance PR_S value of each item participated by each person by the time of participated item, and summing all the products to obtain the item participated degree WP_S value of each person, wherein the calculation formula is as follows:
WP_S(i)＝SUM j (TP_S(i,j)*PR_S(j))
wherein wp_s (i) represents the item participation degree of the ith person, tp_s (i, j) represents the time period of participation of the ith person in the jth item, pr_s (j) represents the importance degree of the jth item, the persons are ranked from high to low according to the item participation degree wp_s value, and rp_s (i) represents the item participation degree ranking of the ith person.
10. The method for analyzing the relationship between office workers according to claim 9, wherein in the step 2, the degree of item correlation between the workers is calculated as follows:
finding out matters which two persons participate in together, and calculating the relation degree WP_SR value of the matters between the two persons, wherein the calculation formula is as follows:
WP_SR(i,k)＝SUM j (TP_S(i,j)*PR_S(j)*TP_S(k,j))
wherein wp_sr (i, k) represents the degree to which the ith person is related to the item of the kth person, pr_s (j) represents the degree of importance of the jth item, tp_s (i, j) represents the length of time for which the ith person participates in the jth item, tp_s (k, j) represents the length of time for which the kth person participates in the jth item;
ranking the item correlations of each person with other persons from high to low by the item correlation wp_sr value, the rank of the jth person in the item correlations of the ith person is denoted rp_sr (i, j).
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| CN111694963A (en) * | 2020-05-11 | 2020-09-22 | 电子科技大学 | Key government affair flow identification method and device based on item association network |
| CN111695003A (en) * | 2020-05-11 | 2020-09-22 | 电子科技大学 | Government affair shared material identification method and system based on item association network |
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| WO2011056231A1 (en) * | 2009-11-06 | 2011-05-12 | Bryan Cave Llp | Systems and methods for providing business rankings |
| CN111694963A (en) * | 2020-05-11 | 2020-09-22 | 电子科技大学 | Key government affair flow identification method and device based on item association network |
| CN111695003A (en) * | 2020-05-11 | 2020-09-22 | 电子科技大学 | Government affair shared material identification method and system based on item association network |
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