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Cross-social-network user identification method based on full-view features

A technology for social network and user identification, applied in the field of data mining and data integration of social networks, can solve the problems of computing influence, computing detachment, cold start and so on, and achieve the effect of improving the accuracy rate and recall rate

Active Publication Date: 2017-12-15
NORTHEASTERN UNIV
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Problems solved by technology

[0005] The existing hybrid social network user matching research mainly considers the processing of information characteristics of social networks, and there are some shortcomings: first, it is the cold start problem
If the heuristic algorithm is used blindly to solve the problem, the calculation

Method used

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Embodiment Construction

[0027] Attached below Figure 1-3 As well as specific embodiments, the present invention is further described in detail.

[0028] image 3 Among them, GAUI is the method designed and implemented in this paper, and the rest are existing methods.

[0029] As shown in Table 1, there are user sample datasets from different social networks SA and SB. There are 5 users u1...u5 on the social network SA, and 5 users r1...r5 on the social network SB. The corresponding complete and correct user identification results should be {{u2,r5},{u3,r2},{u4,r3},{u5,r4}}. Where {u3, r2}, {u5, r4} are known user identification pairs. It is hoped that when identifying as many social network users representing the same entity as possible, the accuracy of identification is also improved as much as possible.

[0030] Table 1 social network user data set, including 10 user records, attributes include name, age, job and city.

[0031]

[0032]

[0033] First, the full-view feature similarity ca...

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Abstract

The invention discloses a cross-social-network user identification method based on full-view features. First, community division is carried out on multiple social networks, and reference points are initialized. Then, the following three steps are carried out iteratively: (1) the full-view features of unidentified users are calculated using the reference points in order to calculate the similarity between users; (2) users are identified using an improved stable marriage matching algorithm; and (3) for a newly identified user pair, a reference point set is updated according to the centrality of communities. The three steps are repeated constantly until the reference point set is no longer updated, and a matching anchor link user set is obtained. On one hand, the cross-social-network user identification method of the invention considers the global locations of users in social networks, and is of higher accuracy and recall rate of user identification. In addition, through an iteratively adjusted identification strategy, the problem on how to correctly identify multiple similar user pairs is solved, and the problem of cold start is avoided.

Description

technical field [0001] The invention belongs to the field of data mining and data integration of social networks, and mainly relates to a cross-social network user identification method based on full view features. Background technique [0002] With the development of the Internet, more and more people have established various virtual accounts on the Internet. Different from traditional SMS (Short Message Service) and other applications, social networks, as a product of the WEB2.0 era, focus on social attributes and provide people with a wealth of social services, such as using social networks to share news, transfer knowledge, publish topics, etc. . Most of them will communicate with friends through multiple social networks, but different accounts of users are not related to each other because they are distributed on different social networks. Being able to fuse these online networks into a single environment can help users stay connected while also providing a way for us...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06Q50/00
CPCG06Q50/01G06F18/22
Inventor 申德荣汪潜聂铁铮寇月于戈
Owner NORTHEASTERN UNIV
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