Automatic Acquisition of Semantic Relationships from Morphological Relatedness
Identifieur interne : 002C32 ( Istex/Corpus ); précédent : 002C31; suivant : 002C33Automatic Acquisition of Semantic Relationships from Morphological Relatedness
Auteurs : Delphine BernhardSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: Semantic relationships like specialisation can be acquired either by word-external methods relying on the context or word-internal methods based on lexical structure. Word segments are thus a relevant cue for the automatic acquisition of semantic relationships. We have developed an unsupervised method for morphological segmentation devised for this objective. Semantic relationships are deduced from specific morphological structures based on the segments discovered. Evaluation of the validity of the semantic relationships inferred is performed against WordNet and the NCI Thesaurus.
Url:
DOI: 10.1007/11816508_14
Links to Exploration step
ISTEX:5ECC7246FE8573F50D5FEB0A363827749D453706Le document en format XML
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type="first">Sampo</forename><surname>Pyysalo</surname></persName><email>Sampo.Pyysalo@it.utu.fi</email><affiliation>Turku Centre for Computer Science (TUCS) and Department of IT, University of Turku, Lemminkäisenkatu 14 A, 20520, Turku, Finland</affiliation></editor><editor xml:id="serie-author-0020"><persName><forename type="first">Tapio</forename><surname>Pahikkala</surname></persName><email>Tapio.Pahikkala@utu.fi</email><affiliation>Department of Information Technology, University of Turku, Lemminkäisenkatu 14–18 A, FIN-20520, Turku, Finland</affiliation></editor><idno type="pISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><biblScope unit="seriesId">1244</biblScope></series></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2006</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Abstract: Semantic relationships like specialisation can be acquired either by word-external methods relying on the context or word-internal methods based on lexical structure. Word segments are thus a relevant cue for the automatic acquisition of semantic relationships. We have developed an unsupervised method for morphological segmentation devised for this objective. Semantic relationships are deduced from specific morphological structures based on the segments discovered. Evaluation of the validity of the semantic relationships inferred is performed against WordNet and the NCI Thesaurus.</p></abstract><textClass><keywords scheme="Book-Subject-Collection"><list><label>SUCO11645</label><item><term>Computer Science</term></item></list></keywords></textClass><textClass><keywords scheme="Book-Subject-Group"><list><label>I</label><item><term>Computer Science</term></item><label>I21017</label><item><term>Artificial Intelligence (incl. 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Proceedings</BookSubTitle><BookVolumeNumber>4139</BookVolumeNumber><BookSequenceNumber>4139</BookSequenceNumber><BookDOI>10.1007/11816508</BookDOI><BookTitleID>140777</BookTitleID><BookPrintISBN>978-3-540-37334-6</BookPrintISBN><BookElectronicISBN>978-3-540-37336-0</BookElectronicISBN><BookChapterCount>75</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2006</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I21017" Priority="1" Type="Secondary">Artificial Intelligence (incl. 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Word segments are thus a relevant cue for the automatic acquisition of semantic relationships. We have developed an unsupervised method for morphological segmentation devised for this objective. Semantic relationships are deduced from specific morphological structures based on the segments discovered. Evaluation of the validity of the semantic relationships inferred is performed against WordNet and the NCI Thesaurus.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Automatic Acquisition of Semantic Relationships from Morphological Relatedness</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Automatic Acquisition of Semantic Relationships from Morphological Relatedness</title></titleInfo><name type="personal"><namePart type="given">Delphine</namePart><namePart type="family">Bernhard</namePart><affiliation>TIMC-IMAG, Institut de l’Ingénierie et de l’Information de Santé, Faculté de Médecine, 38706 cedex, La Tronche, France</affiliation><affiliation>E-mail: Delphine.Bernhard@imag.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2006</dateIssued><copyrightDate encoding="w3cdtf">2006</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Semantic relationships like specialisation can be acquired either by word-external methods relying on the context or word-internal methods based on lexical structure. Word segments are thus a relevant cue for the automatic acquisition of semantic relationships. We have developed an unsupervised method for morphological segmentation devised for this objective. Semantic relationships are deduced from specific morphological structures based on the segments discovered. Evaluation of the validity of the semantic relationships inferred is performed against WordNet and the NCI Thesaurus.</abstract><relatedItem type="host"><titleInfo><title>Advances in Natural Language Processing</title><subTitle>5th International Conference on NLP, FinTAL 2006 Turku, Finland, August 23-25, 2006 Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Tapio</namePart><namePart type="family">Salakoski</namePart><affiliation>Turku Centre for Computer Science (TUCS), Department of Information Technology, University of Turku, Joukahaisenkatu 3-5 B, FIN-20520, Turku, Finland</affiliation><affiliation>E-mail: Tapio.Salakoski@it.utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Filip</namePart><namePart type="family">Ginter</namePart><affiliation>Turku Centre for Computer Science (TUCS) and Department of IT, University of Turku, Lemminkäisenkatu 14 A, 20520, Turku, Finland</affiliation><affiliation>E-mail: Filip.Ginter@it.utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Sampo</namePart><namePart type="family">Pyysalo</namePart><affiliation>Turku Centre for Computer Science (TUCS) and Department of IT, University of Turku, Lemminkäisenkatu 14 A, 20520, Turku, Finland</affiliation><affiliation>E-mail: Sampo.Pyysalo@it.utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Tapio</namePart><namePart type="family">Pahikkala</namePart><affiliation>Department of Information Technology, University of Turku, Lemminkäisenkatu 14–18 A, FIN-20520, Turku, Finland</affiliation><affiliation>E-mail: Tapio.Pahikkala@utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="book-series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2006</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book-Subject-Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book-Subject-Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. 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Finland</affiliation><affiliation>E-mail: Filip.Ginter@it.utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Sampo</namePart><namePart type="family">Pyysalo</namePart><affiliation>Turku Centre for Computer Science (TUCS) and Department of IT, University of Turku, Lemminkäisenkatu 14 A, 20520, Turku, Finland</affiliation><affiliation>E-mail: Sampo.Pyysalo@it.utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Tapio</namePart><namePart type="family">Pahikkala</namePart><affiliation>Department of Information Technology, University of Turku, Lemminkäisenkatu 14–18 A, FIN-20520, Turku, Finland</affiliation><affiliation>E-mail: Tapio.Pahikkala@utu.fi</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="sub-series"></genre><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SubSeriesID">1244</identifier></relatedItem><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SeriesID">558</identifier><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2006</recordOrigin></recordInfo></relatedItem><identifier type="istex">5ECC7246FE8573F50D5FEB0A363827749D453706</identifier><identifier type="DOI">10.1007/11816508_14</identifier><identifier type="ChapterID">14</identifier><identifier type="ChapterID">Chap14</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag Berlin Heidelberg, 2006</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 2006</recordOrigin></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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