"All You Can Eat" Ontology-Building Feeding Wikipedia to Cyc

In order to achieve genuine web intelligence, building some kind of large general machine-readable conceptual scheme (i.e. ontology) seems inescapable. Yet the past 20 years have shown that manual ontology-building is not practicable. The recent explosion of free user-supplied knowledge on the Web h...

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Vydané v:Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 Ročník 1; s. 341 - 348
Hlavní autori: Sarjant, Samuel, Legg, Catherine, Robinson, Michael, Medelyan, Olena
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Washington, DC, USA IEEE Computer Society 15.09.2009
IEEE
Edícia:ACM Conferences
Predmet:
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Semantic networks
Computing methodologies > Machine learning > Machine learning approaches > Rule learning
Conferences
Cyc
Hafnium
Helium
Information systems > Information retrieval
Information systems > Information retrieval > Evaluation of retrieval results
Information systems > Information systems applications > Data mining
Intelligent agent
Ontologies
Ontology
Web Mining
Wikipedia
Wikipedia
Ontology
Cyc
Web Mining
ISBN:0769538010, 9780769538013
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Popis
Shrnutí:In order to achieve genuine web intelligence, building some kind of large general machine-readable conceptual scheme (i.e. ontology) seems inescapable. Yet the past 20 years have shown that manual ontology-building is not practicable. The recent explosion of free user-supplied knowledge on the Web has led to great strides in automatic ontology-building, but quality-control is still a major issue. Ideally one should automatically build onto an already intelligent base. We suggest that the long-running Cyc project is able to assist here. We describe methods used to add 35K new concepts mined from Wikipedia to collections in ResearchCyc entirely automatically. Evaluation with 22 human subjects shows high precision both for the new concepts’ categorization, and their assignment as individuals or collections. Most importantly we show how Cyc itself can be leveraged for ontological quality control by ‘feeding’ it assertions one by one, enabling it to reject those that contradict its other knowledge.
ISBN:0769538010
9780769538013
DOI:10.1109/WI-IAT.2009.60