Super-large scale user social network analysis and family relationship identification algorithm based on contact frequency and contact index

Abstract

The invention relates to the field of application of service provider social circle word-of-mouth marketing and family package recommendation marketing, particularly relates to a social network construction and family relationship identification method in word-of-mouth marketing, and discloses a user social network and family relationship construction method through user voice and short and multimedia message contact information. The method comprises the steps of calculation of the contact index, construction of a contact circle model, construction of a social network model and construction of a family relationship identification model. According to the technical scheme, the problems of efficient and robust construction of the social network and family relationship identification based on the contact information under the condition of large data volume of telephone bills of service providers can be solved.

Description

technical field [0001] The invention relates to the application field of word-of-mouth marketing in social circles of operators and recommended marketing of family packages, in particular to methods for building social networks and identifying family relationships in word-of-mouth marketing; Background technique [0002] In the Internet era, the traditional single-customer large-scale mass marketing method has been difficult to attract users, the return on marketing costs is low, and it is easy to cause user complaints; [0003] In the prior art, since the marketing recommendation is mainly for a single customer, there are the following defects in the marketing recommendation process: [0004] 1) Single-customer group marketing is likely to arouse user resentment and cause user complaints; [0005] 2) Do not understand the characteristics of the customer group, and cannot grasp the interest points of the group; [0006] 3) If you don't know the family composition, you can'...

AI Technical Summary

Problems solved by technology

[0004] 1) Single-customer group marketing is likely to arouse user resentment and cause user complaints;

[0005] 2) Do not understand the characteristics of the customer group, and cannot grasp the interest points of the group;

[0006] 3) If you don't know the family composition, you can't recommend family packages in a targeted manner;

[0007] 4) There is no suitable entry point for cross-network marketing;

[0008] In short, the existing mass marketing for single customers is poorly targeted, the cost-return rate is low, and it is easy to cause user complaints;

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