CN112163885A - User relationship mining method and system based on mobile communication data - Google Patents
User relationship mining method and system based on mobile communication data Download PDFInfo
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Abstract
The invention relates to a user relationship mining method and a system based on mobile communication data, wherein the method comprises the following steps of S1, acquiring package information and call ticket data of a plurality of users, filtering and sorting the package information and the call ticket data of each user, and correspondingly acquiring an information set of each user; s2, processing the information sets of any two users to obtain the similarity of the information sets of any two users; and S3, mining the degree of affinity and sparseness of the corresponding two user relations according to the similarity. The method and the system of the invention analyze the relationship between the users by using the package information and the ticket data in the mobile communication data, and can obtain the relationship between the users, thereby providing accurate service for the later marketing.
Description
Technical Field
The invention relates to the field of mobile communication, in particular to a user relationship mining method and system based on mobile communication data.
Background
The competition of domestic telecommunication services has been expanded, and the family and group user markets are the latest market for each large operator and the new income growth point for development. How to accurately identify the family users in the massive user groups, analyze the service behavior characteristics of the family users and carry out effective marketing on the family users is a topic which needs to be solved currently.
Disclosure of Invention
The invention aims to solve the technical problem of providing a user relationship mining method and a user relationship mining system based on mobile communication data, which can mine the relationship among users and provide accurate service for later-stage marketing.
The technical scheme for solving the technical problems is as follows: a user relationship mining method based on mobile communication data comprises the following steps,
s1, acquiring package information and call ticket data of a plurality of users, and filtering and sorting the package information and the call ticket data of each user to correspondingly obtain an information set of each user;
s2, processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and S3, mining the degree of affinity and sparseness of the corresponding two user relations according to the similarity.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, before the S1, S0 is further included;
and S0, collecting sample data, and training the initial relationship model by using the sample data to obtain a target relationship model.
Further, in S2, specifically,
and processing the information sets of any two users by using the target relation model to obtain the similarity of the information sets of any two users.
Further, the sample data comprises a plurality of sample users, package information and ticket data of each sample user, and a user relationship between every two sample users.
Further, in S3, specifically,
and matching the similarity with a preset relation comparison table, and mining the degree of affinity and sparseness of the corresponding two user relations.
Based on the user relationship mining method based on the mobile communication data, the invention also provides a user relationship mining system based on the mobile communication data.
A user relationship mining system based on mobile communication data comprises the following modules,
the system comprises an information set acquisition module, a service information acquisition module and a service information processing module, wherein the information set acquisition module is used for acquiring package information and call ticket data of a plurality of users, filtering and sorting the package information and the call ticket data of each user and correspondingly acquiring an information set of each user;
the similarity calculation module is used for processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and the relationship mining module is used for mining the degree of intimacy and disambiguation of the corresponding two user relationships according to the similarity.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the system also comprises a relation model training module;
and the relation model training module is used for acquiring sample data and training the initial relation model by using the sample data to obtain a target relation model.
Further, the similarity calculation module is specifically configured to,
and processing the information sets of any two users by using the target relation model to obtain the similarity of the information sets of any two users.
Further, the sample data comprises a plurality of sample users, package information and ticket data of each sample user, and a user relationship between every two sample users.
Further, the relationship mining module is specifically configured to,
and matching the similarity with a preset relation comparison table, and mining the degree of affinity and sparseness of the corresponding two user relations.
The invention has the beneficial effects that: the method and the system of the invention analyze the relationship between the users by using the package information and the ticket data in the mobile communication data, and can obtain the relationship between the users, thereby providing accurate service for the later marketing.
Drawings
FIG. 1 is a flow chart of a user relationship mining method based on mobile communication data according to the present invention;
fig. 2 is a block diagram of a user relationship mining system based on mobile communication data according to the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, a method for mining user relationship based on mobile communication data includes the following steps,
s1, acquiring package information and call ticket data of a plurality of users, and filtering and sorting the package information and the call ticket data of each user to correspondingly obtain an information set of each user;
s2, processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and S3, mining the degree of affinity and sparseness of the corresponding two user relations according to the similarity.
In this embodiment, the following preferred embodiments are also provided:
preferably, before said S1, S0 is further included; and S0, collecting sample data, and training the initial relationship model by using the sample data to obtain a target relationship model.
Preferably, in S2, the information sets of any two users are processed by using the target relationship model, so as to obtain the similarity between the information sets of any two users.
Preferably, the sample data includes a plurality of sample users, package information and ticket data of each sample user, and also includes a user relationship between every two sample users.
Preferably, the S3 is specifically configured to match the similarity with a preset affinity-sparseness relationship comparison table, and dig out the affinity-sparseness of the two corresponding user relationships.
Based on the user relationship mining method based on the mobile communication data, the invention also provides a user relationship mining system based on the mobile communication data.
As shown in fig. 2, a system for mining user relationship based on mobile communication data includes the following modules,
the system comprises an information set acquisition module, a service information acquisition module and a service information processing module, wherein the information set acquisition module is used for acquiring package information and call ticket data of a plurality of users, filtering and sorting the package information and the call ticket data of each user and correspondingly acquiring an information set of each user;
the similarity calculation module is used for processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and the relationship mining module is used for mining the degree of intimacy and disambiguation of the corresponding two user relationships according to the similarity.
In this embodiment, the following preferred embodiments are also provided:
preferably, the system further comprises a relation model training module; and the relation model training module is used for acquiring sample data and training the initial relation model by using the sample data to obtain a target relation model.
Preferably, the similarity calculation module is specifically configured to process the information sets of any two users by using the target relationship model, so as to obtain the similarity between the information sets of any two users.
Preferably, the sample data includes a plurality of sample users, package information and ticket data of each sample user, and also includes a user relationship between every two sample users.
Preferably, the relationship mining module is specifically configured to match the similarity with a preset affinity-sparseness relationship comparison table, and mine the affinity-sparseness degree of the two corresponding user relationships.
The method and the system of the invention analyze the relationship between the users by using the package information and the ticket data in the mobile communication data, and can obtain the relationship between the users, thereby providing accurate service for the later marketing.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A user relationship mining method based on mobile communication data is characterized in that: comprises the following steps of (a) carrying out,
s1, acquiring package information and call ticket data of a plurality of users, and filtering and sorting the package information and the call ticket data of each user to correspondingly obtain an information set of each user;
s2, processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and S3, mining the degree of affinity and sparseness of the corresponding two user relations according to the similarity.
2. The method of claim 1, wherein the mining method comprises: prior to said S1, further comprising S0;
and S0, collecting sample data, and training the initial relationship model by using the sample data to obtain a target relationship model.
3. The method of claim 2, wherein the mining method comprises: specifically, the step S2 is,
and processing the information sets of any two users by using the target relation model to obtain the similarity of the information sets of any two users.
4. The method of claim 2 or 3, wherein the mining method comprises the following steps: the sample data comprises a plurality of sample users, package information and ticket data of each sample user, and user relationship between every two sample users.
5. The method of any of claims 1 to 3 for user relationship mining based on mobile communication data, characterized in that: specifically, the step S3 is,
and matching the similarity with a preset relation comparison table, and mining the degree of affinity and sparseness of the corresponding two user relations.
6. A user relationship mining system based on mobile communication data is characterized in that: comprises the following modules which are used for realizing the functions of the system,
the system comprises an information set acquisition module, a service information acquisition module and a service information processing module, wherein the information set acquisition module is used for acquiring package information and call ticket data of a plurality of users, filtering and sorting the package information and the call ticket data of each user and correspondingly acquiring an information set of each user;
the similarity calculation module is used for processing the information sets of any two users to obtain the similarity of the information sets of any two users;
and the relationship mining module is used for mining the degree of intimacy and disambiguation of the corresponding two user relationships according to the similarity.
7. The mobile communication data-based user relationship mining system of claim 6, wherein: the system also comprises a relation model training module;
and the relation model training module is used for acquiring sample data and training the initial relation model by using the sample data to obtain a target relation model.
8. The mobile communication data-based user relationship mining system of claim 7, wherein: the similarity calculation module is specifically configured to,
and processing the information sets of any two users by using the target relation model to obtain the similarity of the information sets of any two users.
9. The system according to claim 7 or 8, wherein: the sample data comprises a plurality of sample users, package information and ticket data of each sample user, and user relationship between every two sample users.
10. The system according to any one of claims 6 to 8, wherein: the relationship mining module is specifically configured to,
and matching the similarity with a preset relation comparison table, and mining the degree of affinity and sparseness of the corresponding two user relations.
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| CN109829485A (en) * | 2019-01-08 | 2019-05-31 | 科大国创软件股份有限公司 | A kind of user relationship mining method and system based on mobile data |
| CN110677269A (en) * | 2018-07-03 | 2020-01-10 | 中国电信股份有限公司 | Method and device for determining communication user relationship and computer readable storage medium |
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- 2020-09-29 CN CN202011054350.8A patent/CN112163885A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106228371A (en) * | 2016-07-18 | 2016-12-14 | 南京坦道信息科技有限公司 | A kind of social network analysis based on the ultra-large user associating frequency and associate index and family relation recognizer |
| CN110677269A (en) * | 2018-07-03 | 2020-01-10 | 中国电信股份有限公司 | Method and device for determining communication user relationship and computer readable storage medium |
| CN109829485A (en) * | 2019-01-08 | 2019-05-31 | 科大国创软件股份有限公司 | A kind of user relationship mining method and system based on mobile data |
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