Pattern-based semantic tagging for ontology population

Authors:
Masumi Inaba;Takayuki Iida;Tomohiro Yamasaki;Kosei Fume;Yumiko Mizoguchi;Shinichi Nagano;Takahiro Kawamura
Affiliations:
Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan;Corporate Research & Development Center, Toshiba Corporation, Kawasaki-shi, Kanagawa, Japan
Venue:
SOCASE'08 Proceedings of the 2008 AAMAS international conference on Service-oriented computing: agents, semantics, and engineering
Year:
2008

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Abstract

Ontology population has emerged as an increasingly importantproblem in semantic web services. In this paper, we propose a method usingnamed entity recognition that extracts keywords from Web pages in order topopulate a product ontology. The semantic classification determines meaningsof terms and phrases by heuristic rules after the morphological analysis. Inaddition, our method classifies vocabularies into different semantic tags. Firstly,it records several lists of semantic tags to a history database. Then, we definesome rules from the lists to extract a product name. Finally, the rules build andrefine the product ontology semi-automatically. According to an evaluation,proposed method achieved 87.1% precision and 87.4% recall. Thus, it cansuggest some instances, and it decreases cost of updating the ontology.