标题:Summary Generation for Temporal Extractions
作者:Wang, Yafang; Ren, Zhaochun; Theobald, Martin; Dylla, Maximilian; de Melo, Gerard
通讯作者:Wang, Yafang
作者机构:[Wang, Yafang] Shandong Univ, Jinan, Peoples R China.; [Ren, Zhaochun] Univ Amsterdam, Amsterdam, Netherlands.; [Theobald, Martin] Univ Ulm, Ulm, 更多
会议名称:27th International Conference on Database and Expert Systems Applications (DEXA)
会议日期:SEP 05-08, 2016
来源:DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2016, PT I
出版年:2016
卷:9827
页码:370-386
DOI:10.1007/978-3-319-44403-1_23
关键词:Temporal information extraction; Knowledge harvesting; Summarization
摘要:Recent advances in knowledge harvesting have enabled us to collect large amounts of facts about entities from Web sources. A good portion of these facts have a temporal scope that, for example, allows us to concisely capture a person's biography. However, raw sets of facts are not well suited for presentation to human end users. This paper develops a novel abstraction-based method to summarize a set of facts into natural-language sentences. Our method distills temporal knowledge from Web documents and generates a concise summary according to a particular user's interest, such as, for example, a soccer player's career. Our experiments are conducted on biography-style Wikipedia pages, and the results demonstrate the good performance of our system in comparison to existing text-summarization methods.
收录类别:CPCI-S;EI;SCOPUS
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84981165059&doi=10.1007%2f978-3-319-44403-1_23&partnerID=40&md5=8712674cb6eeca7c20b66ce85c236baa
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