DocumentCode :
1798671
Title :
Topic model-based micro-blog user interest analysis
Author :
Xinchen Hu ; Dequan Zheng ; Wanglong Sun ; Sheng Li
Author_Institution :
MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., Harbin, China
fYear :
2014
fDate :
7-9 July 2014
Firstpage :
443
Lastpage :
448
Abstract :
As a popular Internet information exchange platform, Micro-Blog like Twitter attracts a large amount of users to share information through short and noisy messages. In this paper, we aim to discover Micro-Blog users´ interest using topic model. In the topic model, users´ metadata such as labels are taken as new features and been put into user document which will be used to infer user´s interest. Experimental results indicate that this method gives satisfying user interest and is capable for reality project. This paper also introduce two applications based on user interest detected before: 1) Keywords extraction based on interest (We calculate word entropy using word topic distribution as new feature). 2) User clustering based on user interest.
Keywords :
Internet; entropy; meta data; pattern clustering; social networking (online); Internet information exchange platform; Twitter; keywords extraction; metadata; microblog user interest analysis; topic model; user clustering; user interest detection; user interest discovery; word entropy; word topic distribution; Analytical models; Data models; Entropy; Load modeling; Semantics; Training; Training data; microblog; topic model; user interest;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-3902-2
Type :
conf
DOI :
10.1109/ICALIP.2014.7009833
Filename :
7009833
Link To Document :
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