Finding relevant relations in relevant documents

Schuhmacher, Michael ; Roth, Benjamin ; Ponzetto, Simone Paolo ; Dietz, Laura

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URN: urn:nbn:de:bsz:180-madoc-412959
Document Type: Conference or workshop publication
Year of publication: 2016
Book title: Advances in Information Retrieval : 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016. Proceedings
The title of a journal, publication series: Lecture Notes in Computer Science
Volume: 9626
Page range: 654-660
Conference title: 38th European Conference on IR Research, ECIR 2016
Location of the conference venue: Padua, Italy
Date of the conference: March 20-23, 2016
Publisher: Ferro, Nicola
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-319-30670-4 , 978-3-319-30671-1
ISSN: 0302-9743 , 1611-3349
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject: 004 Computer science, internet
Abstract: This work studies the combination of a document retrieval and a relation extraction system for the purpose of identifying query-relevant relational facts. On the TREC Web collection, we assess extracted facts separately for correctness and relevance. Despite some TREC topics not being covered by the relation schema, we find that this approach reveals relevant facts, and in particular those not yet known in the knowledge base DBpedia. The study confirms that mention frequency, document relevance, and entity relevance are useful indicators for fact relevance. Still, the task remains an open research problem.

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