Deriving a large scale taxonomy from Wikipedia

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Deriving a large scale taxonomy from Wikipedia
Authors: Simone Paolo Ponzetto, Michael Strube [edit item]
Citation: AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 2 : 1440-1445. 2007 July 22-26. Vancouver, BC, Canada. American Association for Artificial Intelligence.
Publication type: Conference paper
Peer-reviewed: Yes
Database(s):
DOI: Define doi.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Deriving a large scale taxonomy from Wikipedia is a publication by Simone Paolo Ponzetto, Michael Strube.


[edit] Abstract

We take the category system in Wikipedia as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexico-syntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations. We evaluate the quality of the created resource by comparing it with ResearchCyc, one of the largest manually annotated ontologies, as well as computing semantic similarity between words in benchmarking datasets.

[edit] Research questions

"We take the category system inWikipedia as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexicosyntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations."

Research details

Topics: Semantic relatedness [edit item]
Domains: Computer science [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment [edit item]
Data source: Experiment responses, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article [edit item]
Wikipedia data extraction: Dump [edit item]
Wikipedia page type: Article, Information categorization and navigation [edit item]
Wikipedia language: English [edit item]

[edit] Conclusion

"Our Wikipedia- based taxonomy proved to be competitive with the two arguably largest and best developed existing ontologies. We believe that these results are caused by taking already structured and well-maintained knowledge as input."

[edit] Comments

""Our Wikipedia-based taxonomy proved to be competitive with the two arguably largest and best developed existing ontologies. We believe that these results are caused by taking already structured and well-maintained knowledge as input." p. 1445"


Further notes[edit]

Facts about "Deriving a large scale taxonomy from Wikipedia"RDF feed
AbstractWe take the category system in Wikipedia aWe take the category system in Wikipedia as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexico-syntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations. We evaluate the quality of the created resource by comparing it with ResearchCyc, one of the largest manually annotated ontologies, as well as computing semantic similarity between words in benchmarking datasets.ty between words in benchmarking datasets.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
Comments"Our Wikipedia-based taxonomy proved to be competitive with the two arguably largest and best developed existing ontologies. We believe that these results are caused by taking already structured and well-maintained knowledge as input." p. 1445
ConclusionOur Wikipedia-

based taxonomy proved to be competitive with the two arguably largest and best developed existing ontologies. We believe that these results are caused by taking already structured

and well-maintained knowledge as input.
Conference locationVancouver, BC, Canada +
Data sourceExperiment responses + and Wikipedia pages +
Dates22-26 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Deriving%2Ba%2Blarge%2Bscale%2Btaxonomy%2Bfrom%2BWikipedia%22 +
Has authorSimone Paolo Ponzetto + and Michael Strube +
Has domainComputer science +
Has topicSemantic relatedness +
MonthJuly +
Pages1440-1445 +
Peer reviewedYes +
Publication typeConference paper +
Published inAAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 +
PublisherAmerican Association for Artificial Intelligence +
Research designExperiment +
Research questionsWe take the category system inWikipedia asWe take the category system inWikipedia as a conceptual network.

We label the semantic relations between categories using methods based on connectivity in the network and lexicosyntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations.mount of subsumption,

i.e. isa, relations.
Revid10,732 +
TheoriesUndetermined
Theory typeDesign and action +
TitleDeriving a large scale taxonomy from Wikipedia
Unit of analysisArticle +
Urlhttp://en.scientificcommons.org/43568891 +
Volume2 +
Wikipedia coverageSample data +
Wikipedia data extractionDump +
Wikipedia languageEnglish +
Wikipedia page typeArticle + and Information categorization and navigation +
Year2007 +