PERSONALIZED MULTI-DOCUMENT SUMMARIZATION IN INFORMATION RETRIEVAL
This research Is directed towards automating open-domain Multi-Document Summarization in the framework of Web search. We present a novel approach to achieve this object. Given an unrestricted user query, our system retrieves documents related to and summarizes them. In the process of summarization, the sentences in a given document are scored based on the relevant value and the informstiveness value, which are realized by using word overlap and semantic graph. Then, the sentences with highest scores are incorporated into the output summary together with their structural context. Experimental results show that our query-topic focused summary could return a topically relevant extractive summary. And the summarization quality is relatively competitive.
Multi-Document Summarization The Relevant Value Web Page Summarization The Informativcncss Value
XIAO-PENG YANG XIAO-RONG LIU
Jiujiang University, Jiujiang, 332005, Jiangxi, China Network and Information Center, East China Institute of Technology, Fuzhou, 344000, Jiangxi, China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
4108-4112
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）