Difference between revisions of "Automatic Extraction of Semantic Relations from Wikipedia"

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== Overview ==
 
== Overview ==
 
Authors introduce a novel approach to extract semantic relations (e.g., is-a and part-of relations) from [[Wikipedia]] articles. These relations are used to build up a large and up-to-date thesaurus providing background knowledge for tasks such as determining semantic [[ontology]] mappings. Authors automatic approach uses a comprehensive set of semantic patterns, finite state machines and NLP techniques to extract millions of relations between concepts. An evaluation for different domains shows the high quality and effectiveness of the proposed approach. Authors also illustrate the value of the newly found relations for improving existing ontology mappings.
 
Authors introduce a novel approach to extract semantic relations (e.g., is-a and part-of relations) from [[Wikipedia]] articles. These relations are used to build up a large and up-to-date thesaurus providing background knowledge for tasks such as determining semantic [[ontology]] mappings. Authors automatic approach uses a comprehensive set of semantic patterns, finite state machines and NLP techniques to extract millions of relations between concepts. An evaluation for different domains shows the high quality and effectiveness of the proposed approach. Authors also illustrate the value of the newly found relations for improving existing ontology mappings.
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== Embed ==
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=== Wikipedia Quality ===
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Arnold, Patrick; Rahm, Erhard. (2015). "[[Automatic Extraction of Semantic Relations from Wikipedia]]". World Scientific Publishing Company. DOI: 10.1142/S0218213015400102.
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=== English Wikipedia ===
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{{cite journal |last1=Arnold |first1=Patrick |last2=Rahm |first2=Erhard |title=Automatic Extraction of Semantic Relations from Wikipedia |date=2015 |doi=10.1142/S0218213015400102 |url=https://wikipediaquality.com/wiki/Automatic_Extraction_of_Semantic_Relations_from_Wikipedia |journal=World Scientific Publishing Company}}
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=== HTML ===
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Arnold, Patrick; Rahm, Erhard. (2015). &amp;quot;<a href="https://wikipediaquality.com/wiki/Automatic_Extraction_of_Semantic_Relations_from_Wikipedia">Automatic Extraction of Semantic Relations from Wikipedia</a>&amp;quot;. World Scientific Publishing Company. DOI: 10.1142/S0218213015400102.
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Revision as of 07:41, 20 May 2020


Automatic Extraction of Semantic Relations from Wikipedia
Authors
Patrick Arnold
Erhard Rahm
Publication date
2015
DOI
10.1142/S0218213015400102
Links
Original

Automatic Extraction of Semantic Relations from Wikipedia - scientific work related to Wikipedia quality published in 2015, written by Patrick Arnold and Erhard Rahm.

Overview

Authors introduce a novel approach to extract semantic relations (e.g., is-a and part-of relations) from Wikipedia articles. These relations are used to build up a large and up-to-date thesaurus providing background knowledge for tasks such as determining semantic ontology mappings. Authors automatic approach uses a comprehensive set of semantic patterns, finite state machines and NLP techniques to extract millions of relations between concepts. An evaluation for different domains shows the high quality and effectiveness of the proposed approach. Authors also illustrate the value of the newly found relations for improving existing ontology mappings.

Embed

Wikipedia Quality

Arnold, Patrick; Rahm, Erhard. (2015). "[[Automatic Extraction of Semantic Relations from Wikipedia]]". World Scientific Publishing Company. DOI: 10.1142/S0218213015400102.

English Wikipedia

{{cite journal |last1=Arnold |first1=Patrick |last2=Rahm |first2=Erhard |title=Automatic Extraction of Semantic Relations from Wikipedia |date=2015 |doi=10.1142/S0218213015400102 |url=https://wikipediaquality.com/wiki/Automatic_Extraction_of_Semantic_Relations_from_Wikipedia |journal=World Scientific Publishing Company}}

HTML

Arnold, Patrick; Rahm, Erhard. (2015). &quot;<a href="https://wikipediaquality.com/wiki/Automatic_Extraction_of_Semantic_Relations_from_Wikipedia">Automatic Extraction of Semantic Relations from Wikipedia</a>&quot;. World Scientific Publishing Company. DOI: 10.1142/S0218213015400102.