Automatic selection of defining vocabulary in an explanatory dictionary

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

One of the problems in converting a conventional (human-oriented) explanatory dictionary into a semantic database intended for the use in automatic reasoning systems is that such a database should not contain any cycles in its definitions, while the traditional dictionaries usually contain them. The cycles can be eliminated by declaring some words “primitive” (having no definition) while all other words are defined in terms of these ones. A method for detecting the cycles in definitions and selecting a minimal (though not the smallest) defining vocabulary is presented. Different strategies for selecting the words for the defining vocabulary are discussed and experimental data for a real dictionary are presented.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 3rd International Conference, CICLing 2002, Proceedings
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages300-303
Number of pages4
ISBN (Print)3540432191, 9783540457152
DOIs
StatePublished - 2002
Event3rd Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2002 - Mexico City, Mexico
Duration: 17 Feb 200223 Feb 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2276
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2002
Country/TerritoryMexico
CityMexico City
Period17/02/0223/02/02

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