A similarity-based approach for ontology mapping

Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorit...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Wu Ya-Juan, Lang Ji-Sheng, Shang Fu-Hua
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 169
container_issue
container_start_page 165
container_title
container_volume
creator Wu Ya-Juan
Lang Ji-Sheng
Shang Fu-Hua
description Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorithm of concept similarity is proposed in this paper. An advanced measure of setting candidate mapping set is applied to reduce the runtime of the account. The presented algorithm involves concept name, attribute, structure and instance levels. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.
doi_str_mv 10.1109/ICCSE.2009.5228502
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5228502</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5228502</ieee_id><sourcerecordid>5228502</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-803966f5fc9772764196a1d056fa7635bcaa046b08da2a54a59a74715cbecefa3</originalsourceid><addsrcrecordid>eNo1T8FqwzAU8xiFrV1-YLvkB5I9O352fCyhWwuFHbbBbuXFsTuPpAlxLvn7BdbpIiQkgRh75JBzDub5UFXvu1wAmByFKBHEDUuMLrkUUhYoONyy9b-ArxVbL9nS8KUMdyyJ8QcWSBRGqHsG2zSGLrQ0hmnOaoquSWkYxp7sd-r7Me0vU9_25zntFjtczg9s5amNLrnyhn2-7D6qfXZ8ez1U22MWuMYpK6EwSnn01mgttJLcKOINoPKkVYG1JQKpaigbEoSS0JCWmqOtnXWeig17-tsNzrnTMIaOxvl0fVz8AtJHRtM</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A similarity-based approach for ontology mapping</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Wu Ya-Juan ; Lang Ji-Sheng ; Shang Fu-Hua</creator><creatorcontrib>Wu Ya-Juan ; Lang Ji-Sheng ; Shang Fu-Hua</creatorcontrib><description>Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorithm of concept similarity is proposed in this paper. An advanced measure of setting candidate mapping set is applied to reduce the runtime of the account. The presented algorithm involves concept name, attribute, structure and instance levels. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.</description><identifier>ISBN: 142443520X</identifier><identifier>ISBN: 9781424435203</identifier><identifier>EISBN: 9781424435210</identifier><identifier>EISBN: 1424435218</identifier><identifier>DOI: 10.1109/ICCSE.2009.5228502</identifier><identifier>LCCN: 2008911100</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial intelligence ; Candidate Mapping Set ; Computer science ; Computer science education ; Knowledge management ; Ontologies ; Ontology Interoperability ; Ontology Mapping ; Petroleum ; Runtime ; Semantic Web ; Software engineering ; Thesauri</subject><ispartof>2009 4th International Conference on Computer Science &amp; Education, 2009, p.165-169</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5228502$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>310,311,781,785,790,791,2059,27930,54925</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5228502$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wu Ya-Juan</creatorcontrib><creatorcontrib>Lang Ji-Sheng</creatorcontrib><creatorcontrib>Shang Fu-Hua</creatorcontrib><title>A similarity-based approach for ontology mapping</title><title>2009 4th International Conference on Computer Science &amp; Education</title><addtitle>ICCSE</addtitle><description>Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorithm of concept similarity is proposed in this paper. An advanced measure of setting candidate mapping set is applied to reduce the runtime of the account. The presented algorithm involves concept name, attribute, structure and instance levels. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.</description><subject>Artificial intelligence</subject><subject>Candidate Mapping Set</subject><subject>Computer science</subject><subject>Computer science education</subject><subject>Knowledge management</subject><subject>Ontologies</subject><subject>Ontology Interoperability</subject><subject>Ontology Mapping</subject><subject>Petroleum</subject><subject>Runtime</subject><subject>Semantic Web</subject><subject>Software engineering</subject><subject>Thesauri</subject><isbn>142443520X</isbn><isbn>9781424435203</isbn><isbn>9781424435210</isbn><isbn>1424435218</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1T8FqwzAU8xiFrV1-YLvkB5I9O352fCyhWwuFHbbBbuXFsTuPpAlxLvn7BdbpIiQkgRh75JBzDub5UFXvu1wAmByFKBHEDUuMLrkUUhYoONyy9b-ArxVbL9nS8KUMdyyJ8QcWSBRGqHsG2zSGLrQ0hmnOaoquSWkYxp7sd-r7Me0vU9_25zntFjtczg9s5amNLrnyhn2-7D6qfXZ8ez1U22MWuMYpK6EwSnn01mgttJLcKOINoPKkVYG1JQKpaigbEoSS0JCWmqOtnXWeig17-tsNzrnTMIaOxvl0fVz8AtJHRtM</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Wu Ya-Juan</creator><creator>Lang Ji-Sheng</creator><creator>Shang Fu-Hua</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200907</creationdate><title>A similarity-based approach for ontology mapping</title><author>Wu Ya-Juan ; Lang Ji-Sheng ; Shang Fu-Hua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-803966f5fc9772764196a1d056fa7635bcaa046b08da2a54a59a74715cbecefa3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Artificial intelligence</topic><topic>Candidate Mapping Set</topic><topic>Computer science</topic><topic>Computer science education</topic><topic>Knowledge management</topic><topic>Ontologies</topic><topic>Ontology Interoperability</topic><topic>Ontology Mapping</topic><topic>Petroleum</topic><topic>Runtime</topic><topic>Semantic Web</topic><topic>Software engineering</topic><topic>Thesauri</topic><toplevel>online_resources</toplevel><creatorcontrib>Wu Ya-Juan</creatorcontrib><creatorcontrib>Lang Ji-Sheng</creatorcontrib><creatorcontrib>Shang Fu-Hua</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wu Ya-Juan</au><au>Lang Ji-Sheng</au><au>Shang Fu-Hua</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A similarity-based approach for ontology mapping</atitle><btitle>2009 4th International Conference on Computer Science &amp; Education</btitle><stitle>ICCSE</stitle><date>2009-07</date><risdate>2009</risdate><spage>165</spage><epage>169</epage><pages>165-169</pages><isbn>142443520X</isbn><isbn>9781424435203</isbn><eisbn>9781424435210</eisbn><eisbn>1424435218</eisbn><abstract>Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorithm of concept similarity is proposed in this paper. An advanced measure of setting candidate mapping set is applied to reduce the runtime of the account. The presented algorithm involves concept name, attribute, structure and instance levels. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.</abstract><pub>IEEE</pub><doi>10.1109/ICCSE.2009.5228502</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 142443520X
ispartof 2009 4th International Conference on Computer Science & Education, 2009, p.165-169
issn
language eng
recordid cdi_ieee_primary_5228502
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Artificial intelligence
Candidate Mapping Set
Computer science
Computer science education
Knowledge management
Ontologies
Ontology Interoperability
Ontology Mapping
Petroleum
Runtime
Semantic Web
Software engineering
Thesauri
title A similarity-based approach for ontology mapping
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-15T02%3A15%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20similarity-based%20approach%20for%20ontology%20mapping&rft.btitle=2009%204th%20International%20Conference%20on%20Computer%20Science%20&%20Education&rft.au=Wu%20Ya-Juan&rft.date=2009-07&rft.spage=165&rft.epage=169&rft.pages=165-169&rft.isbn=142443520X&rft.isbn_list=9781424435203&rft_id=info:doi/10.1109/ICCSE.2009.5228502&rft_dat=%3Cieee_6IE%3E5228502%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781424435210&rft.eisbn_list=1424435218&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5228502&rfr_iscdi=true