Learning Conflict Resolution Strategies for Cross-language Wikipedia Data Fusion

Bryl, Volha ; Bizer, Christian

DOI: https://doi.org/10.1145/2567948.2578999
URL: http://www.dl.kuis.kyoto-u.ac.jp/webquality2014/p1...
Additional URL: http://dws.informatik.uni-mannheim.de/fileadmin/le...
Document Type: Conference or workshop publication
Year of publication: 2014
Book title: 23rd International World Wide Web Conference, WWW '14, Seoul, Republic of Korea, April 7-11, 2014, Companion Volume
Page range: 1129-1134
Conference title: 4th Workshop on Web Quality (WebQuality2014)
Date of the conference: April 2014
Publisher: Chung, Chin-Wan
Place of publication: New York, NY
Publishing house: ACM
ISBN: 978-1-4503-2745-9
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems V: Web-based Systems (Bizer 2012-)
Subject: 004 Computer science, internet
Keywords (English): Data Fusion, Data Integration, Wikipedia
Abstract: In order to efficiently use the ever growing amounts of structured data on the web, methods and tools for quality-aware data integration should be devised. In this paper we propose an approach to automatically learn the conflict resolution strategies, which is a crucial step in large-scale data integration. The approach is implemented as an extension of the Sieve data quality assessment and fusion framework. We apply and evaluate our approach on the use case of fusing data from 10 language editions of DBpedia, a large-scale structured knowledge base extracted from Wikipedia. We also propose a method for extracting rich provenance metadata for each DBpedia fact, which is later used in data fusion.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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