Volume 9 Number 9 (Sep. 2014)
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JSW 2014 Vol.9(9): 2246-2250 ISSN: 1796-217X
doi: 10.4304/jsw.9.9.2246-2250

Wikipedia Based Approach for Clustering Keyword of Reviews

Ming Jiang1, 2, Wencao Yan1, 2, Xingqi Wang1, 2, Jingfan Tang1, 2, Chunming Wu3

1Institute of Software and Intelligent Technology, Hangzhou Dianzi University, Hangzhou, 310018, China
2Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis, Hangzhou Dianzi University, Hangzhou, 310018, China
3College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China


Abstract—A novel method based on Wikipedia for clustering keyword of reviews is proposed. Users can quickly finding the themes they interest through it. First the method extracts keywords, then calculates word similarity based on Wikipedia to generate similarity matrix, finally uses k-means to cluster. The performance is better than the methods which based on How-net and Word-net. The accuracy is around 77%.

Index Terms—Wikipedia, keyword of reviews, semantic similarity, similarity matrix, cluster

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Cite: Ming Jiang, Wencao Yan, Xingqi Wang, Jingfan Tang, Chunming Wu, "Wikipedia Based Approach for Clustering Keyword of Reviews," Journal of Software vol. 9, no. 9, pp. 2246-2250, 2014.

General Information

  • ISSN: 1796-217X (Online)
  • Frequency:  Quarterly
  • Editor-in-Chief: Prof. Antanas Verikas
  • Executive Editor: Ms. Yoyo Y. Zhou
  • Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
  • E-mail: jsweditorialoffice@gmail.com
  • APC: 500USD
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