关键词: 本体学习, 非监督学习, 关联规则, 非分类关系, VF*ICF度量法, 对数似然比

Abstract: Research on non-taxonomical relations from domain concepts is an important task in ontology learning. This paper presents an acquiring method for non-taxonomical relations of special domain based on unsupervised learning. This method employs association rules to get the concept pairs of special domain, regards the high frequency verbs of the concept pairs as the candidate non-taxonomical relations labels, non-taxonomical relations labels is determined by VF*ICF metrics, use log likelihood ratio to assign the non-taxonomical relations labels to corresponding domain concepts pairs. Experimental results demonstrate the increment of the accuracy and completeness of the non-taxonomical relations extraction.

Key words: ontology learning, unsupervised learning, association rules, non-taxonomical relations, VF*ICF metrics, Log likelihood ratio