Unsupervised document summarization from data reconstruction perspective-Reference-Cited by-同舟云学术

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Unsupervised document summarization from data reconstruction perspective

Published:2015-06 Issue: Volume:157 Page:356-366
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

He Zhanying,Chen Chun,Bu Jiajun,Wang Can,Zhang Lijun,Cai Deng,He Xiaofei

Funder

National Basic Research Program of China (973 Program)

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Foundation of Zhejiang Provincial Educational Department

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

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2. S. Brin, L. Page, The anatomy of a large-scale hypertextual web search engine, Comput. Netw. doi:http://dx.doi.org/10.1016/j.comnet.2012.10.007.

3. Authoritative sources in a hyperlinked environment;Kleinberg;J. ACM,1999

4. X. Wan, J. Yang, Collabsum: exploiting multiple document clustering for collaborative single document summarizations, in: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ׳07, ACM, 2007, pp. 143–150. doi:http://dx.doi.org/10.1145/1277741.1277768.

5. J.M. Conroy, D.P. O׳leary, Text summarization via hidden Markov models, in: Proceedings of the 24th Annual International ACM SIGIR conference on Research and Development in Information Retrieval, SIGIR ׳01, ACM, 2001, pp. 406–407.

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3. BHLM: Bayesian theory-based hybrid learning model for multi-document summarization;International Journal of Modeling, Simulation, and Scientific Computing;2018-03-20

4. KeyphraseDS: Automatic generation of survey by exploiting keyphrase information;Neurocomputing;2017-02

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