Enriching structured knowledge with open information
Dutta, Arnab
;
Meilicke, Christian
;
Stuckenschmidt, Heiner
DOI:
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https://doi.org/10.1145/2736277.2741139
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URL:
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https://ub-madoc.bib.uni-mannheim.de/38861
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Additional URL:
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http://dl.acm.org/citation.cfm?id=2741139
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URN:
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urn:nbn:de:bsz:180-madoc-388619
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Document Type:
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Conference or workshop publication
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Year of publication:
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2015
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Book title:
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Proceedings of the 24th International Conference on World Wide Web, {WWW} 2015, Florence, Italy, May 18-22, 2015
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Page range:
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267-277
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Date of the conference:
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18-22 May 2015
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Publisher:
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Gangemi, Aldo
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Place of publication:
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New York, NY
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Publishing house:
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ACM
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ISBN:
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978-1-4503-3469-3
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
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Subject:
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004 Computer science, internet
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Keywords (English):
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Markov clustering , data integration , enriching knowledge bases , probabilistic inference
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Abstract:
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We propose an approach for semantifying web extracted facts. In particular, we map subject and object terms of these facts to instances; and relational phrases to object properties defined in a target knowledge base. By doing this we resolve the ambiguity inherent in the web extracted facts, while simultaneously enriching the target knowledge base with a significant number of new assertions. In this paper, we focus on the mapping of the relational phrases in the context of the overall work ow. Furthermore, in an open extraction setting identical semantic relationships can be represented by different surface forms, making it necessary to group these surface forms together. To solve this problem we propose the use of markov clustering. In this work we present a complete, ontology independent, generalized workflow which we evaluate on facts extracted by Nell and Reverb. Our target knowledge base is DBpedia. Our evaluation shows promising results in terms of producing highly precise facts. Moreover, the results indicate that the clustering of relational phrases pays of in terms of an improved instance and property mapping.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
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