ISCAS OpenIR  > 基础软件与系统重点实验室
exploiting novelty, coverage and balance for topic-focused multi-document summarization
Li Xuan; Shen Yi-Dong; Du Liang; Xiong Chen-Yan
2010
Conference Name19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
SourceInternational Conference on Information and Knowledge Management, Proceedings
Pages1765-1768
Conference Date40842
Conference PlaceToronto, ON, Canada
Indexed TypeEI
Publish PlaceUnited States
ISBN9781450000000
Department(1) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Graduated University, Chinese Academy of Sciences, Beijing 100049, China
English AbstractNovelty, coverage and balance are important requirements in topic-focused summarization, which to a large extent determine the quality of a summary. In this paper, we propose a novel method that incorporates these requirements into a sentence ranking probability model. It differs from the existing methods in that the novelty, coverage and balance requirements are all modeled w.r.t. a given topic, so that summaries are highly relevant to the topic and at the same time comply with topic-aware novelty, coverage and balance. Experimental results on the DUC 2005, 2006 and 2007 benchmark data sets demonstrate the effectiveness of our method. © 2010 ACM.
SponsorshipACM SIGIR; ACM SIGWEB; ACM SIGKDD
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8752
Collection基础软件与系统重点实验室
Recommended Citation
GB/T 7714
Li Xuan,Shen Yi-Dong,Du Liang,et al. exploiting novelty, coverage and balance for topic-focused multi-document summarization[C]. United States,2010:1765-1768.
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