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Microblog Topic Mining Method Based on Dynamic Behavior of Heterogeneous Social Media Users

A user and heterogeneous technology, applied in data processing applications, special data processing applications, unstructured text data retrieval, etc., can solve problems such as ignoring social network heterogeneity and diversity, and achieve the effect of enriching context information

Active Publication Date: 2021-12-07
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] Although the above methods have achieved good performance, multiple interactions between users, such as forwarding, commenting, following, and mentioning, should be treated equally [1] , ignoring the influence of the heterogeneity and diversity of social networks on microblog topic inference

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  • Microblog Topic Mining Method Based on Dynamic Behavior of Heterogeneous Social Media Users
  • Microblog Topic Mining Method Based on Dynamic Behavior of Heterogeneous Social Media Users
  • Microblog Topic Mining Method Based on Dynamic Behavior of Heterogeneous Social Media Users

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Embodiment Construction

[0067] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments described here are only used to explain the present invention, not to limit the present invention.

[0068] Taking 3 real microblog data sets as examples, the specific implementation method of the present invention is given. The overall framework of the method is as follows figure 1 shown. The algorithm flow of the whole system includes three steps: attribute multivariate heterogeneous dialogue network input, learning the embedding of specific views, and topic generation based on multi-view neural variational reasoning.

[0069] Specific steps are as follows:

[0070] (1) Attribute Multivariate Heterogeneous Dialogue Network Input

[0071] On the Sina Weibo platform, the predecessors used the topic index search application programming interface (hashtag-search API) to co...

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Abstract

The invention discloses a microblog topic mining method based on the dynamic behavior of heterogeneous social media users, comprising the following steps: constructing a multi-attribute heterogeneous dialogue network, mining heterogeneous social context for topic detection; introducing a neighbor-level attention mechanism and The interaction-level attention mechanism models the different influences of different neighbors and different types of interactions on topic inference, and learns the embedding of specific views; the representation of multiple views is used as the input of multi-view neural variational reasoning, and captures the topic semantics carried by different views. complex associations to mine more consistent themes.

Description

technical field [0001] The invention relates to the technical fields of natural language processing and social media data mining, in particular to a microblog topic mining method based on dynamic behaviors of heterogeneous social media users. Background technique [0002] The emergence of social media sites (such as Sina Weibo, etc.) has greatly changed the form of content on the Internet. Weibo allows users to publish and browse information on it, and has strong social attribute functions, such as forwarding and commenting. A large amount of text data is stored on the Weibo platform, and it grows at an alarming rate every day. Microblog text content contains a large amount of information, mining topic information from it can be used for topic recommendation, emergency detection, precision marketing, etc. At present, text topic mining technology has achieved good results when applied to long text data such as news and articles. However, the length of microblog text is rel...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F40/216G06F40/30G06Q50/00G06K9/62
CPCG06F16/355G06F40/216G06F40/30G06Q50/01G06F18/25
Inventor 贺瑞芳刘宏宇朱永凯王浩成韩迪
Owner TIANJIN UNIV
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