Ontology-based adaptation of vector space model for e-commerce product information retrieval

摘要

With the rapid development of e-commerce, online shopping has become an important part in people's lives, how to provide users with an efficient and practical product information search method has become an urgent and critical problem. This paper proposes an ontology-based adaptation of the classical Vector Space Model with the consideration of the weight of product attribute. In this proposal, domain ontology is adopted to extract concepts from documents, thus product documents can be translated into feature vectors that compose the concept based vector space. Experiments to measure retrieval efficiency have been performed. The experimental result indicates that the proposed approach is better than the traditional keywords based search.