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Exploiting multilinguality for creating mappings between thesauri

Published: 13 April 2015 Publication History

Abstract

The definition of mappings between multilingual thesauri is a recent research topic concerning the application of the traditional schema mapping algorithms in conjunction with the use of multilingual resources. In this paper, we present a multilingual mapping approach aiming at defining matches between terms belonging to multilingual thesauri. The paper presents the approach as a variant of the schema mapping problem and discusses its evaluation on (i) domain-specific use cases and (ii) on a standard benchmark, namely MultiFarm benchmark, used for measuring the effectiveness of multilingual ontology mapping systems.

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  • (2020)Combining Machine Learning and Natural Language Processing for Language-Specific, Multi-Lingual, and Cross-Lingual Text SummarizationTrends and Applications of Text Summarization Techniques10.4018/978-1-5225-9373-7.ch001(1-31)Online publication date: 2020

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cover image ACM Conferences
SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing
April 2015
2418 pages
ISBN:9781450331968
DOI:10.1145/2695664
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 the author(s) 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: 13 April 2015

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April 13 - 17, 2015
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SAC '15 Paper Acceptance Rate 291 of 1,211 submissions, 24%;
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  • (2020)Combining Machine Learning and Natural Language Processing for Language-Specific, Multi-Lingual, and Cross-Lingual Text SummarizationTrends and Applications of Text Summarization Techniques10.4018/978-1-5225-9373-7.ch001(1-31)Online publication date: 2020

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