JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (09): 36-41.doi: 10.6040/j.issn.1671-9352.3.2014.287

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Micro-blogging topic mining based on supervised LDA user interest model

WANG Li-ren1,2, YU Zheng-tao1,2, WANG Yan-bing1,2, GAO Sheng-xiang1,2, LI Xian-hui1,2   

  1. 1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, Yunnan, China;
    2. Intelligent Information Processing Key Laboratory, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • Received:2015-03-03 Revised:2015-07-22 Online:2015-09-20 Published:2015-09-26

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Abstract: The content of users Micro-blogging can reflect users' interests. Forwarding, commenting, replying and other behavior about Micro-blogging have a strong guiding role to discovering users' interests. In order to using Micro-blogging behavior effectively, we proposed users' interest modeling method based on supervised-LDA Micro-blogging contents. First of all,through analyzing the impact elements, including forwarding, commenting, replying, and other behavior, four constraint relations were defined. Second, based on the contents of Micro-blogging, the four constraint relations were put into the LDA model and the supervised-LDA Micro-blogging theme generation model were constructed. And then the distribution of the users' theme and the users' interests' model were obtained. The experimental results show that compared with the LDA method, this model has high accuracy, and the four introduced guiding information have a significant role in discovering Micro-blogging users' interests.

Key words: interest in mining, Micro-blogging behavior, supervised LDA, Micro-blogging content

CLC Number: 

  • TP393
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