Conceptual analysis of lexical taxonomies: the case of WordNet top-level
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Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
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ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
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Deriving a large scale taxonomy from Wikipedia
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WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
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Information Retrieval
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CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
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Artificial Intelligence
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DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
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AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
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This paper presents an automatic method for differentiating between instances and classes in a large scale taxonomy induced from the Wikipedia category network. The method exploits characteristics of the category names and the structure of the network. The approach we present is the first attempt to make this distinction automatically in a large scale resource. In contrast, this distinction has been made in WordNet and Cyc based on manual annotations. The result of the process is evaluated against ResearchCyc. On the subnetwork shared by our taxonomy and ResearchCyc we report 84.52% accuracy.