Document (#40185)

Author

Pandey, S.
Khanna, P.
Yokota, H.

Title

¬A semantics and image retrieval system for hierarchical image databases

Source

Information processing and management. 52(2016) no.4, S.571-591

Year

2016

Abstract

General graph random walk has been successfully applied in multi-document summarization, but it has some limitations to process documents by this way. In this paper, we propose a novel hypergraph based vertex-reinforced random walk framework for multi-document summarization. The framework first exploits the Hierarchical Dirichlet Process (HDP) topic model to learn a word-topic probability distribution in sentences. Then the hypergraph is used to capture both cluster relationship based on the word-topic probability distribution and pairwise similarity among sentences. Finally, a time-variant random walk algorithm for hypergraphs is developed to rank sentences which ensures sentence diversity by vertex-reinforcement in summaries. Experimental results on the public available dataset demonstrate the effectiveness of our framework.

Content

Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457315001429.

Form

Bilder

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2. Chang, Y.-W.: Influence of human behavior and the principle of least effort on library and information science research (2016) 3.34

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3. Vilares, J.; Alonso, M.A.; Doval, Y.; Vilares, M.: Studying the effect and treatment of misspelled queries in Cross-Language Information Retrieval (2016) 3.34

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4. Ouyang, Y.; Li, W.; Li, S.; Lu, Q.: Intertopic information mining for query-based summarization (2010) 0.20

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5. Wei, F.; Li, W.; Lu, Q.; He, Y.: Applying two-level reinforcement ranking in query-oriented multidocument summarization (2009) 0.17

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