doi: 10.4304/jsw.6.12.2407-2415
Topic Detection with Hypergraph Partition Algorithm
- 1 School of Computer Science and Technology, Dalian University of Technology, Dalian, China
- 2 School 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.
Keywords
- topic detection
- similarity matrix
- hype
How to Cite
Xinyue Liu, Fenglong Ma, and Hongfei Lin, "Topic Detection with Hypergraph Partition Algorithm," Journal of Software, vol. 6, no. 12, pp. 2407-2415, 2011. https://doi.org/ 10.4304/jsw.6.12.2407-2415
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).