Volume 6 Number 12 (Dec. 2011)
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JSW 2011 Vol.6(12): 2407-2415 ISSN: 1796-217X
doi: 10.4304/jsw.6.12.2407-2415

Topic Detection with Hypergraph Partition Algorithm

Xinyue Liu1, 2, Fenglong Ma2, Hongfei Lin1
1School of Computer Science and Technology, Dalian University of Technology, Dalian, China
2School of Software, Dalian University of Technology, Dalian, China

Abstract—An algorithm named SMHP (Similarity Matrix based Hypergraph Partition) algorithm is proposed, which aims at improving the efficiency of Topic Detection. In SMHP, a T-MI-TFIDF model is designed by introducing Mutual Information (MI) and enhancing the weight of terms in the title. Then Vector Space Model (VSM) is constructed according to terms' weight, and the dimension is reduced by combining H-TOPN and Principle Component Analysis (PCA). Then topics are grouped based on SMHP. Experiment results show the proposed methods are more suitable for clustering topics. SMHP with novel approaches can effectively solve the relationship of multiple stories problem and improve the accuracy of cluster results.

Index Terms—topic detection, similarity matrix, hypergraph partition, clustering


Cite: Xinyue Liu, Fenglong Ma, Hongfei Lin, "Topic Detection with Hypergraph Partition Algorithm," Journal of Software vol. 6, no. 12, pp. 2407-2415, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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