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Target-Oriented Keyword Search over Temporal Databases Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Summary Generation for Temporal Extractions

Authors : Yafang Wang, Zhaochun Ren, Martin Theobald, Maximilian Dylla, Gerard de Melo

Published in: Database and Expert Systems Applications

Publisher: Springer International Publishing

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Abstract

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.

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Footnotes
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Metadata
Title
Summary Generation for Temporal Extractions
Authors
Yafang Wang
Zhaochun Ren
Martin Theobald
Maximilian Dylla
Gerard de Melo
Copyright Year
2016
Book
Database and Expert Systems Applications

Print ISBN: 978-3-319-44402-4

Electronic ISBN: 978-3-319-44403-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-44403-1_23

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