Ontology Evolution for Customer Services

Abstract

Customer service support has become an integral part of many multinational manufacturing companies which produce insertion and surface mount machines in the electronics industry. With the recent advancement of the Semantic Web, many attempts have been made to provide customer support over the Semantic Web environment. Ontology is the major factor to represent knowledge on the Semantic Web. Therefore, a specific ontology socalled Machine Ontology is required to render customer service support with precise semantics. Machine Ontology can be generated either manually by human experts or automatically by intelligent programs. Even though manual ontology generation is highly accurate, it is tedious, time-consuming and requires high cost in terms of man power. On the other hand, automatic generation of ontology can provide high level of knowledge details and be effective when dealing with large-scaled dataset. However, automatically generated ontology may be not very semantically correct. In order to tackle this problem, this paper proposes an ontology evolution technique that can enhance manual ontology with additional in-depth knowledge previously discovered in an automatic manner. The ontology evolution technique is based on the concept of ontology integration. The proposed technique has been applied to evolve Machine Ontology which is used to support customer service for industry manufacturers in Singapore. Some experimental results are also presented.