JSW 2013 Vol.8(1): 192-199 ISSN: 1796-217X
doi: 10.4304/jsw.8.1.192-199
doi: 10.4304/jsw.8.1.192-199
Statistical Methods based on Semantic Similarity of Topics Related to Microblogging
Dongqing Wu, Fengjian Yang, Chaolong Zhang
Computation Science Department , Zhongkai University of Agriculture and Engineering, Guangzhou
Guangdong 510225
Abstract—Existing topic tracking methods are mostly for news and forum data, which lack of statistical methods for microblogging on relevant topics. Combined with characteristics of micro-blog information, the paper proposes a microblogging statistical methods based on semantic similarity. Firstly by building topic semantic model and then use the HowNet semantic similarity calculation of two terms, and measures the relevance of the topic and microblogging. Finally statistics method is provided on the degree of correlation. Experiments show that novel method works on the problem soundly.
Index Terms—Microblogging topic, semantic similarity, HowNet, LSI, statistical methods.
Abstract—Existing topic tracking methods are mostly for news and forum data, which lack of statistical methods for microblogging on relevant topics. Combined with characteristics of micro-blog information, the paper proposes a microblogging statistical methods based on semantic similarity. Firstly by building topic semantic model and then use the HowNet semantic similarity calculation of two terms, and measures the relevance of the topic and microblogging. Finally statistics method is provided on the degree of correlation. Experiments show that novel method works on the problem soundly.
Index Terms—Microblogging topic, semantic similarity, HowNet, LSI, statistical methods.
Cite: Dongqing Wu, Fengjian Yang, Chaolong Zhang, "Statistical Methods based on Semantic Similarity of Topics Related to Microblogging," Journal of Software vol. 8, no. 1, pp. 192-199, 2013.
PREVIOUS PAPER
A Method of Hot Topic Detection in Blogs Using N-gram Model
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
-
Mar 01, 2024 News!
Vol 19, No 1 has been published with online version [Click]
-
Jan 04, 2024 News!
JSW will adopt Article-by-Article Work Flow
-
Apr 01, 2024 News!
Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec) [Click]
-
Apr 01, 2024 News!
Papers published in JSW Vol 18, No 1- Vol 18, No 6 have been indexed by DBLP [Click]
-
Nov 02, 2023 News!
Vol 18, No 4 has been published with online version [Click]