Document Summarization via Self-Present Sentence Relevance Model-Reference-Cited by-同舟云学术

Document Summarization via Self-Present Sentence Relevance Model

Published:2013 Issue: Volume: Page:309-323
ISSN:0302-9743
Container-title:Database Systems for Advanced Applications
language:
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Author:

Li Xiaodong,Zhu Shanfeng,Xie Haoran,Li Qing

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-37450-0_24

Reference22 articles.

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2. Conroy, J.M., O’leary, D.P.: Text summarization via hidden markov models. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 406–407. ACM (2001)

3. Dou, S., Sun, J.-T., Li, H., Yang, Q., Chen, Z.: Document summarization using conditional random fields. In: Proceedings of IJCAI, vol. 7, pp. 2862–2867 (2007)

4. Erkan, G., Radev, D.R.: LexRank: Graph-based lexical centrality as salience in text summarization. Journal of Artificial Intelligence Research 22(1), 457–479 (2004)

5. Gong, Y., Liu, X.: Generic text summarization using relevance measure and latent semantic analysis. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 19–25. ACM (2001)

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