Abstract
Graph-based models and ranking algorithms have been drawn considerable attentions from the document summarization community in the recent years. However, in regard to query-oriented summarization, the influence of the query has been limited to the sentence nodes in the previous graph models. We argue that other than the sentence nodes the sentence-sentence edges should also be measured in accordance with the given query. In this paper, we develop a query-sensitive similarity measure that incorporates the query influence into the evaluation of sentence-sentence edges for graph-based queryoriented summarization. Furthermore, in order to cope with the multi-document summarization task, we explicitly distinguish the inter-document sentence relations from the intra-document sentence relations and emphasize the influence of global information from the document set on local sentence evaluation. Experimental results on DUC 2005 dataset are quite promising and motivate us to further investigate query-sensitive similarity measures.
Original language | English |
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Title of host publication | Proceedings - International Symposium on Information Processing, ISIP 2008 and International Pacific Workshop on Web Mining and Web-Based Application, WMWA 2008 |
Pages | 9-13 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 19 Sept 2008 |
Event | International Symposium on Information Processing, ISIP 2008 and International Pacific Workshop on Web Mining and Web-Based Application, WMWA 2008 - Moscow, Russian Federation Duration: 23 May 2008 → 25 May 2008 |
Conference
Conference | International Symposium on Information Processing, ISIP 2008 and International Pacific Workshop on Web Mining and Web-Based Application, WMWA 2008 |
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Country/Territory | Russian Federation |
City | Moscow |
Period | 23/05/08 → 25/05/08 |
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems
- Software