Hypergraph partition with harmonic average top-N and PCA for Topic Detection

Xinyue Liu, Fenglong Ma, Hongfei Lin, Hong Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An algorithm named SMHP 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 VSM is constructed according to terms' weight, and the dimension is reduced by combining H-TOPN and 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.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2010
Pages269-276
Number of pages8
DOIs
StatePublished - Dec 1 2010
Event3rd International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2010 - Dalian, China
Duration: Dec 18 2010Dec 20 2010

Publication series

NameProceedings - 3rd International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2010

Conference

Conference3rd International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2010
CountryChina
CityDalian
Period12/18/1012/20/10

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Hardware and Architecture

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