Similarity Measurement in the Hybrid of Semantic Web Search Engine

Abstract

Semantic Web approach with the assistance of ontology is widely used to give more reliable application in retrieving information and knowledge.  It is capable to discover the World Wide Web (WWW) that is presented in natural-language text.  Based on previous research, incorporating categorization with ontology concept has proven to give better results.  However, performing hybrid of the search engine using another technique that is user profiling has a promising potency in enhancing the searching process.  Utilizing searching time and giving relevant results are the contributions of this research.  The proposed hybrid techniques integrate ontologies, categorization and user profiling concept.  In user profiling, similarity measure is adopted in making comparison between two different ontologies.  WordNet and UTHM Onto are the independent ontologies used in this process.  The preliminary experimental results have given interesting results in terms of data arrangement and time usage.