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Automatic acquisition of taxonomies in different languages from multiple Wikipedia versions

Authors:

Renato Domínguez García,

Christoph Rensing,

Ralf SteinmetzAuthors Info & Claims

i-KNOW '11: Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies

Article No.: 35, Pages 1 - 4

https://doi.org/10.1145/2024288.2024330

Published: 07 September 2011 Publication History

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Abstract

In the last years, the vision of the Semantic Web has led to many approaches that aim to automatically derive knowledge bases from Wikipedia. These approaches rely mostly on the English Wikipedia as it is the largest Wikipedia version and have lead to valuable knowledge bases. However, each Wikipedia version contains socio-cultural knowledge, i.e. knowledge with specific relevance for a culture or language. One difficulty of the application of existing approaches to multiple Wikipedia versions is the use of additional corpora. In this paper, we describe the adaptation of existing heuristics that make the extraction of large sets of hyponymy relations from multiple Wikipedia versions with little information about each language possible. Further, we evaluate our approach with Wikipedia versions in four different languages and compare results with GermaNet for German and WordNet for English.

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Dorado RBramy AMejía-Moncayo CRojas A(2017)Automatic Acquisition of Controlled Vocabularies from Wikipedia Using Wikilinks, Word Ranking, and a Dependency ParserAdvances in Computing10.1007/978-3-319-66562-7_3(32-43)Online publication date: 17-Aug-2017
https://doi.org/10.1007/978-3-319-66562-7_3
Domínguez García RSchmidt SRensing CSteinmetz R(2012)Automatic taxonomy extraction in different languages using wikipedia and minimal language-specific informationProceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I10.1007/978-3-642-28604-9_4(42-53)Online publication date: 11-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28604-9_4

Index Terms

Automatic acquisition of taxonomies in different languages from multiple Wikipedia versions
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Data management systems

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Published In

i-KNOW '11: Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies

September 2011

306 pages

ISBN:9781450307321

DOI:10.1145/2024288

Editors:
Stefanie Lindstaedt
Know-Center Graz, Austria
,
Michael Granitzer
Know-Center Graz, Austria

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 September 2011

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i-KNOW '11

i-KNOW '11: International Conference on Knowledge Management and Technologies

September 7 - 9, 2011

Graz, Austria

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Dorado RBramy AMejía-Moncayo CRojas A(2017)Automatic Acquisition of Controlled Vocabularies from Wikipedia Using Wikilinks, Word Ranking, and a Dependency ParserAdvances in Computing10.1007/978-3-319-66562-7_3(32-43)Online publication date: 17-Aug-2017
https://doi.org/10.1007/978-3-319-66562-7_3
Domínguez García RSchmidt SRensing CSteinmetz R(2012)Automatic taxonomy extraction in different languages using wikipedia and minimal language-specific informationProceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I10.1007/978-3-642-28604-9_4(42-53)Online publication date: 11-Mar-2012
https://dl.acm.org/doi/10.1007/978-3-642-28604-9_4

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Automatic taxonomy extraction in different languages using wikipedia and minimal language-specific information

Wikipedia Mining for Huge Scale Japanese Association Thesaurus Construction

Improving the extraction of bilingual terminology from Wikipedia

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