@inProceedings{
 title = {Deriving a Large Scale Taxonomy from Wikipedia},
 type = {inProceedings},
 year = {2007},
 identifiers = {[object Object]},
 pages = {1440-1445},
 volume = {22},
 issue = {2},
 websites = {http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Deriving+a+Large+Scale+Taxonomy+from+Wikipedia#0},
 publisher = {Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999},
 institution = {Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999},
 id = {62b03b5a-3750-3be2-a4d1-0116afd62e9a},
 created = {2012-02-09T21:39:35.000Z},
 file_attached = {true},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Ponzetto2007},
 private_publication = {false},
 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 lexicosyntactic 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.},
 bibtype = {inProceedings},
 author = {Ponzetto, Simone Paolo and Strube, Michael},
 booktitle = {Artificial Intelligence}
}

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