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A heterogeneous social network user entity anchor link identification method

A social network and user entity technology, applied in the field of heterogeneous social network user entity anchor link identification, can solve the problems of data set dependence, complex implementation process, and inapplicability

Active Publication Date: 2019-06-28
HARBIN ENG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Dong Y et al. used the factor graph model to predict user anchor links in social networks, but due to the complexity of the implementation process and the dependence on the data set, this method is not suitable for all occasions

Method used

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  • A heterogeneous social network user entity anchor link identification method
  • A heterogeneous social network user entity anchor link identification method
  • A heterogeneous social network user entity anchor link identification method

Examples

Experimental program
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Embodiment Construction

[0060] The present invention will be further described below in conjunction with the accompanying drawings.

[0061] 1. Given a heterogeneous social network G, G=(V,E), where node V contains a variety of information nodes, V={V num |num∈Z +}, num represents the type of node, when num=1, the node represents user u and u∈V 1 ; The link E between nodes contains multiple types, num 1 、num 2 Indicates the type of node.

[0062] 2. Given two heterogeneous social networks G 1 and G 2 , the user set is used respectively and express. user anchor link if and only if

[0063] 3. Given two heterogeneous social networks G 1 and G 2 , and User two-dimensional matrix used for user attribute similarity judgment and user relationship similarity judgment respectively, attr={n, a, l, c}, n, a, l, c represent four user attributes respectively: user name, User attribution, user real-time shared location and user published content. Each value in P is and According to th...

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Abstract

The invention belongs to the field of social network analysis, and particularly relates to a heterogeneous social network user entity anchor link identification method, which comprises the following steps of: giving two heterogeneous social networks G1 and G2, and respectively using and representing a user set; calculating user similarity based on user attributes in the two heterogeneous social networks; calculating the user similarity based on the user relationship in the two heterogeneous social networks; performing similarity sorting on the user u and the corresponding intimate friends {fi}, and selecting top K ufi; According to the method, the similarity of the previous common friend relationship is optimized and improved, the intimate friends taking the user attributes as the benchmarks are extracted, the recognition degree of the user anchor link is enhanced through the similarity degree of the intimate friend relationship, and the recognition effect of the user anchor link is greatly improved.

Description

technical field [0001] The invention belongs to the field of social network analysis, and in particular relates to a method for identifying anchor links of heterogeneous social network user entities. Background technique [0002] With the rapid development of the Internet, social networks have gradually entered people's lives, such as Facebook, Twitter, Renren, Sina Weibo, etc. People's use of social networks is not limited to one platform, but uses multiple social platforms at the same time, and the focus of each social platform is different. For example, follow some celebrities, writers, or people and things you are interested in on Twitter, and follow videos on YouTube, or give likes to favorite videos, etc. like figure 1 shown. Each user usually has separate accounts in different social networks, and these accounts of the same user do not appear to have any connection or correspondence with each other. It is necessary to discover the correspondence between different ...

Claims

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Application Information

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IPC IPC(8): G06Q50/00G06F16/951G06F16/9536G06F16/958G06F16/955
Inventor 王巍杨武玄世昌苘大鹏吕继光杨帆
Owner HARBIN ENG UNIV
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