关键词: Web服务参数, 本体学习, 层次Dirichlet过程（HDP）

Abstract: At present, ontologies on the Internet are hard to satisfy the needs of semantic searching on Web services. Manually building ontologies referring to specific application is difficult and costly, so that it is necessary to establish a method of ontology automatically learning from Web service descriptions to facilitate domain experts generating high quality ontologies. In view of these problems, this paper proposes an ontology learning method from Web service descriptions. This method automatically learns ontology hierarchical structures and topics in each level by using topic model based on HDP (hierarchical Dirichlet process). Topics in each level are represented by “representation word” whose calculation is defined. Rules according to parameters composition pattern which define semantic enriching rules are utilized in the bottom-up ontology sematic enriching algorithm. Experiments show that the proposed method is richer in semantics than hHDP (hierarchies of hierarchical Dirichlet process) and better in semantic hierarchies than the method using association rule mining.

Key words: Web service parameter, ontology learning, hierarchical Dirichlet process (HDP)