Automatic text summarization based on sentences clustering and extraction

Proceedings - 2009 2nd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2009

Volumn , Issue , 2009, Pages 167-170

  Zhang, Pei Ying ^a   Li, Cun He ^a  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

Author keywords

Sentence extractive technique; Sentences clustering; Similarity measure; Text summarization

Indexed keywords

AUTOMATIC TEXT SUMMARIZATION; COMBINATION METHOD; DATA SETS; EXTRACTION RULE; INFORMATION CONTENTS; INFORMATION OVERLOADS; MULTIFEATURES; SEMANTIC DISTANCE; SENTENCE SIMILARITY; SIMILARITY MEASURE; TEXT CLASSIFICATION; TEXT SUMMARIZATION;

COMPUTER SCIENCE; INFORMATION TECHNOLOGY; NATURAL LANGUAGE PROCESSING SYSTEMS; TEXT PROCESSING;

INFORMATION RETRIEVAL;

EID: 77954223824     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCSIT.2009.5234971     Document Type: Conference Paper

References (18)

1. Done Zhen-dong. HowNet[OL].http://www.keenage.com
2. Barzilay, Elhadad, 1997. Using lexical chains for text summarization. Proceedings of the ACL'97/EACL'97 Workshop on Intelligent Scalable Text Summarization.
3. Berger and Mittal, 2000. Query-relevant summarization using faqs. Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics.
4. Carbonell, Goldstein, 1998. The use of MMR, diversity-based reranking for reordering documents and producting summaries [A], In: Proceedings of the 21st ACM-SIGIR International Conference on Research and Development in Information Retrieval [C], Melbourne, Australia.
5. Jiang Min, Xiao Shi-bin, Wang Hong-wei et al, 2008. An improved word similarity computing method based on HowNet[J].Journal of Chinese information processing.
6. Goldstein, Kantrowitz, Mittal, and Carbonell, 1999. Summarization text documents: Sentence selection and evaluation metrics. Proceedings SIGIR.
7. Katz, S. M, 1996. Distribution of content words and phrases in text and language modeling. Natural Language Engineering.
8. Klavans, Shaw, 1995. Lexical semantics in summarization. Proceedings of the First Annual Workshop of the IFIP working Group for Natural Language Processing and Knowledge Representation.
9. Mani, 2002. Automatic summarization. A tutorial presented at ICON.
10. Nakao, 2000. An algorithm for one-page summarization for a long text based on thematic hierarchy detection. Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics.
11. Nomoto, Matsumoto, 2001. A new approach to unsupervised text summarization. Proceedings of the 24th ACM SIGIR.
12. Radev, McKeown, 1998. Generating natural language summaries from multiple online sources. Computational Linguistics.
13. Ramiz M. Aliguliyev, 2008. A new sentence similarity measure and sentence based extractive technique for automatic text summarization. Expert System with Applications.
14. Shen, D., Sun, J.-T., Li, H., Yang, Q., & Chen, Z. (2007). Document summarization using conditional random fields. In Proceedings of the 20th international joint conference on artificial intelligence (IJCAI 2007), January 6-12 (pp. 2862-2867) Hyderabad, India
15. Strzalkowski, Wise, Wang, 1998. A robust practical text summarization system. Proceedings of the Fifteenth National Conference on Al.
16. Wan, X. (2008). Using only cross-document relationships for both generic and topic-focused multi-document summarizations. Information Retrieval.
17. Zechner, 1996. Fast generation of abstracts from general domain text corpora by extracting relevant sentences. COLING.
18. Zhang Qi, Huang Xuan-jing, Wu Li-de, 2004. A new method for calculating similarity between sentences and application on automatic text summarization. Journal of Chinese information processing