OSN community discovery method based on LDA Theme model

A topic model and community discovery technology, applied in other database retrieval, semantic analysis, network data retrieval and other directions, can solve the problem of not taking into account the user's topic characteristics, achieve the effect of fast processing and ensure accuracy

Inactive Publication Date: 2016-02-03
SOUTHEAST UNIV
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Problems solved by technology

[0003] The traditional community discovery method is mainly based on the connection, that is, the topological structure of the graph. This method divides the community by analyzing the explicit connection between individuals. The

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  • OSN community discovery method based on LDA Theme model
  • OSN community discovery method based on LDA Theme model
  • OSN community discovery method based on LDA Theme model

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Embodiment Construction

[0033] In the following, the present invention will be further clarified with reference to specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. After reading the present invention, those skilled in the art can make various equivalent changes to the present invention. It falls within the scope defined by the appended claims of this application.

[0034] An OSN community discovery method based on the LDA topic model. First, the data set is preprocessed; then the relationship between the user and his friends in the online social network and the text information spontaneously expressed by the user are used to establish the LDA topic model (including the LDA-F model and the LDA- T model), solve the model probability distribution; then use the Gibbs sampling algorithm to estimate the parameters; finally, perform OSN community discovery based on the estimated parameters,...

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Abstract

The invention discloses an online social network (short for OSN) community discovery method based on a Latent Dirichlet Allocation (short for LDA) theme model. The method comprises the following steps first pre-processing data, building an LDA theme model (including an LDA-F model and an LDA-T model) based on a relationship between a user in the online social network and other friends and word information expressed by the user to solve a model probability distribution, then estimating parameters via a Gibbs sampling algorithm, and at last discovering an OSN community according to the estimated parameters. By the use of the OSN community discovery method based on the LDA Theme model, a corresponding probability model can be achieved based on user blog semantic information discovery without the use of information connection via the network topology; blog content semantic similarities are introduced to effectively describe user interest and hobby probability distribution conditions; and with the introduction of community internal topological connection tightness, communities with close internal topological connections can be discovered.

Description

Technical field [0001] The present invention relates to an online social network (Online Social Network, OSN) community discovery mechanism that utilizes an invisible Dirichlet Allocation (Latent Dirichlet Allocation, LDA) theme model, and belongs to the field of social computing, especially the field of community discovery. Background technique [0002] With the rapid development of the Internet, the network has gradually changed from data-centric to human-centric, which has promoted the rapid development of online social networks. Online social networks are different from traditional interpersonal networks. They not only have large-scale users and their friends, but also have a large number of text messages spontaneously expressed by users, which brings new vitality and challenges to community discovery. [0003] The traditional community discovery method is mainly based on connection, that is, the topological structure of the graph. This method divides the community by analyzing...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27G06Q50/00
CPCG06F16/958G06F40/30G06Q50/01
Inventor 曹玖新马卓陈巧云刘波周涛
Owner SOUTHEAST UNIV
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