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| Recognizing Users’ Focuses on Social Network Based on Mixed-weight Combined Strategy |
| JI Jianrui LIU Yezheng JIANG Yuanchun |
(School of Management, Hefei University of Technology, Hefei 230009, China)
(Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009, China) |
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Abstract It is an important measure to utilize the topic model to recognize the users’ focuses on social networks, such as blog, online community, and microblog. Considering the particularity of topic recognizing of short texts on the social network platform, this paper develops an AW-LDA model based on mixed-weight combined strategy according to the relevance of short texts’ context. This model virtually combines short texts, which are in line with contextual-related conditions, and endows different short texts with different weights according to the related extent. It proposes a new method of recognizing short texts’ topics. According to the experiments on data of BBS and Weibo communities, the results show that the model can effectively recognize social network users’ focuses on different subjects and it proposes a new idea about solving the topic recognition problem of short texts.
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Received: 09 December 2016
Published: 14 June 2017
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| Fund:The National Natural Science Foundation of China (71490725, 71521001, 71371062, 91546114, 71501057), The National 973 Program of China (2013CB329603), The National Key Technology Support Program (2015BAH26F00), MOE Project of Humanities and Social Sciences (15YJC630111) |
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Corresponding Authors:
JIANG Yuanchun
E-mail: ycjiang@hfut.edu.cn
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