Research on text hierarchical topic identification algorithm based on the dynamic diverse thresholds clustering

2009 International Conference on Asian Language Processing: Recent Advances in Asian Language Processing, IALP 2009

Volumn , Issue , 2009, Pages 206-210

  Xu, Yong Dong ^a   Quan, Guang Ri ^a   Xu, Zhi Ming ^a   Wang, Ya Dong ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Hierarchical topic; Multi threshold identification; Text clustering; Text topic identification

Indexed keywords

CLUSTERING METHODS; COMMON PROBLEMS; ENTROPY METHODS; HUMAN EXPERT; MULTITHRESHOLD; TEXT CLUSTERING; TOPIC IDENTIFICATION; TOPIC STRUCTURES; TREE STRUCTURES;

ALGORITHMS; CLUSTER ANALYSIS; LINGUISTICS; TREES (MATHEMATICS);

CHARACTER RECOGNITION;

EID: 77950882984     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IALP.2009.50     Document Type: Conference Paper

References (15)

1. Edmundson H. P. New methods in automatic extracting[J] . Journal of the ACM , 1969 ,16 (2) :264-285.
2. Gerard Salton, James Allan, Chris Buckley, et al. Automatic analysis, theme generation, and summarization of machine-readable texts[J]. Science, 1994, 264 (3):1421-1426.
3. Chang HC, HSU CC. Using topic keyword clusters for automatic document clustering[J]. IEEE Transactions on Information and Systems, 2005, E88 - D (8) : 1852-1860.
4. Sunayama W, Yachida M. Panoramic view system for extracting key sentences based on viewpoints and application to a search engine. Journal of Network and Computer Applications, 2005, 28 (2) : 115-127.
5. Zhong Binbin etc. The Research of Parameter Optimization in Sub-topic Segmentation Based on GA. Computer Engineering and Applications, 2005(21): 97-99
6. Naomi Daniel, Dragomir Radev, and Timothy Allison. Sub-event based multi-document summarization. HLT NAACL Workshop on Text Summarization, 2003 : 9-16
7. E. Filatova, V. Hatzivassilglou, Event-Based Extractive Summarization. In the Proceedings of ACL Workshop on Summarization, Barcelona, Spain, July 2004
8. Endre Boros, Paul B Kantor, David J Neu. A Clustering Based Approach to Creating Multi-Document Summaries .Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New Orleans, LA. 2001,.
9. Pascale Fung. Combining Optimal Clustering and Hidden Markov Model for Extractive Summarization. Proceedings of the ACL 2003 workshop on multilingual summarization and question answering. 2003, pp 21-28.
10. Qin Bing, Liu Ting, Li Sheng. Multi-Documents Summarization Based on Sub-Topics. Proceeding of the NCIRCS 2005. BeiJing, 2005, pp 365-371.
11. Naomi Daniel,Dragomir Radev,and Timothy Allison. Sub-event based multi-document summarization [A]. HLTNAACL Workshop on Text Summarization [C]. Edmonton Alberta.Canada. 2003, pp 9-16.
12. Yu Jun, Yang JianWu, Chen XiaoOu. Multi-document summarization in TDT. Proceedings of the 3rd National Conference on Information Retrieval and Content Security, ShuZhou, 2007
13. H.Zha. Generic Summarization and Key Phrase Extraction Using Mutual Reinforcement Principle and Sentence Clustering. Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval Tampere. Finland. 2002 .
14. XU Yong-Dong etc. Using Multiple Features and Statistical Model To Calculate Text Units Similarity, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics IEEE, Guangzhou, 19-21 August 2005
15. García J.A., Fdez-Valdivia J., Cortijo F. J., and Molina R. 1994. A Dynamic Approach for Clustering Data. Signal Processing, Vol. 44, No. 2, 1994, pp 181-196.