Learning Relation Instances for Chinese Domain Ontology from the Web

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. (C) 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.