Social network group discovery system and method and storage medium

A technology of social network and discovery method, applied in network data retrieval, network data index, biological neural network model, etc., can solve the problems of unsatisfactory calculation results and high calculation time complexity, achieve time complexity optimization and simple evaluation process , strong security effect

Pending Publication Date: 2021-03-05
XI AN JIAOTONG UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0005] Aiming at the deficiencies in the prior art, the object of the present invention is to provide a social network group discovery system, method and storage medium to solve the technical problems in the prior art that the calculation time complexity is too high and the calculation results are not ideal

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  • Social network group discovery system and method and storage medium
  • Social network group discovery system and method and storage medium
  • Social network group discovery system and method and storage medium

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Experimental program
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Embodiment

[0104] A method for discovering social network groups is provided in this embodiment, including the following steps:

[0105] Step 1. Collect online social network datasets and create social network topology maps

[0106] During the collection process, this embodiment uses the direct table lookup method to obtain three data sets of the online network public data sets DIP, Wine and BioGrid. The above data sets are all derived from the UCI machine learning library and related papers on the online network; A number of twitter data; based on the above datasets, an online social network topology map is established, and the online social network topology map is preprocessed to remove data points with low connectivity; all the above datasets are labeled, and the specificity of the dataset The situation is as shown in Table 1;

[0107] Table 1 Collected online social network datasets

[0108]

[0109]

[0110] Step 2. Acquisition of adjacency matrix

[0111] According to the ...

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Abstract

The invention discloses a social network group discovery system and method and a storage medium, and the method comprises the steps: firstly obtaining an online social network data set, and building an online social network topological graph; establishing an adjacent matrix according to the online social network topological graph, and performing dimension reduction processing on the adjacent matrix by utilizing a depth stack type auto-encoder to obtain a dimension reduction matrix; obtaining node embedding vectors by utilizing a graph embedding method; and finally, clustering the node embedding vectors to obtain a clustering result, namely a social network group discovery result. According to the invention, by obtaining the online social network data group and extracting the adjacency matrix, the description of the relationship between online social network users is realized; the integrity of an online social network structure is effectively reserved by utilizing a deep stack type auto-encoder and graph embedding, and the accuracy of a group discovery result is ensured; the node embedding vectors after dimension reduction embedding are clustered to obtain the discovery result, so that the time complexity is reduced, and the discovery result can be obtained more quickly and accurately.

Description

technical field [0001] The technical field of social network analysis of the present invention, in particular, relates to a social network group discovery system, method and storage medium. Background technique [0002] With the popularization of the Internet and the development of online social platforms, various social networks have developed rapidly in online social platforms, such as WeChat social groups, QQ group networks, Weibo hotspot attention networks or Twitter tweeting networks; As far as the Internet is concerned, the discovery of online social networks has become a hot topic in academia and industry. [0003] The traditional social network discovery method is to cluster according to the adjacency relationship between users in the network, and use more complex algorithms to divide users into communities, such as spectral clustering and other methods; if the online social network scale is too large, the spectral The time complexity of clustering calculation is to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/951G06Q50/00G06K9/62G06N3/04
CPCG06F16/9024G06F16/951G06Q50/01G06N3/045G06F18/23213
Inventor 沈超刘笑子刘晓明周亚东管晓宏
Owner XI AN JIAOTONG UNIV
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