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Learning Relation Instances for Chinese Domain Ontology from the Web
Author(s) -
Tian Fang,
Ren Fuji
Publication year - 2010
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20516
Subject(s) - ontology , relation (database) , computer science , relevance (law) , protégé , owl s , information retrieval , domain (mathematical analysis) , semantic web , ontology inference layer , class (philosophy) , ontology learning , world wide web , upper ontology , natural language processing , artificial intelligence , data mining , suggested upper merged ontology , semantic web stack , mathematics , mathematical analysis , philosophy , epistemology , political science , law
This paper presents a method to extract relation instances from the Internet in order to acquire knowledge that has some relations for domain ontology. We propose an ontology relation instance learning model: data sources are collected though the Web search engine and the extracted instances are constructed in Web ontology language (OWL) by Protege in Chinese. Basically, the extraction of relation instances contains syntactic patterns for filtering concepts and relevance measurement for selection of relation instances. A relevance measurement based on co‐occurrence statistics is presented in this paper, which measures the semantic similarity of the measure between candidate instances and predefined domain keywords using Web search engines. In the experiment, we extract festival customs for different festival instances using relation ‘has_custom’ between festival class and custom class in the Chinese festival ontology, and prove the effectiveness of our method. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.