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	Exploring strategies for developing link analysis based question-oriented multi-document summarization models
	Li, Su-Jian ; Wang, Wei ; Li, Wen-Jie
	2011
英文摘要	Graph ranking algorithms have been successfully used in multi-document summarization. Among them, the basic link analysis model has drawn much attention due to its' mutual reinforcement principle which appears to be sound for the generic summarization task. In this paper, we explore effective strategies for extending the basic link analysis model to question-oriented multi-document summarization. Three kinds of strategies, namely link re-weighting, baseset downsizing and projection, are proposed to introduce question-dependent similarity metric, adjust the node number and refine the ranking process respectively. Experimental results evaluated on the DUC data sets demonstrate that these three strategies can achieve better results. ? 2011 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/ICMLC.2011.6016951
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/411303]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Su-Jian,Wang, Wei,Li, Wen-Jie. Exploring strategies for developing link analysis based question-oriented multi-document summarization models. 2011-01-01.

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