Semantic web search engine using ontology, clustering and personalization techniques

Abstract

Data accuracy and reliability have been a serious issue in the vast emergence of information on the web. Advanced web searching has assisted in knowledge retrieving. However, most knowledge on the Web is presented in natural-language text that understandable by human but difficult for computers to interpret. Therefore, Semantic Web approach is widely used to give more reliable application. This paper presents a framework in enhancing knowledge retrieval processes using Semantic Web technologies. Instead of using ontology and categorization alone, we are injecting personalization concept from Relational Database (RDB) to ensure more reliable data are obtained. The proposed framework is discussed in details. A case study is presented to see the viability of the proposed framework in retrieving the meaningful information. © 2012 Springer-Verlag.