Title: An intelligent inventive system for personalised webpage recommendation based on ontology semantics
Authors: Gerard Deepak; Ansaf Ahmed; B. Skanda
Addresses: Department of Computer Science and Engineering, Faculty of Engineering, Christ University, Bangalore, 560074, India ' RSA Business Unit, Dell EMC, Bangalore, 560048, India ' Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, 560001, India
Abstract: Owing to the information diversity in the web and its dynamically changing contents, extraction of relevant information from the web is a huge challenge. With the World Wide Web transforming into a more organised semantic web, the incorporation of semantic techniques to retrieve relevant information is highly necessary. In this paper, a dynamic ontology alignment technique for recommending relevant webpages is proposed. The strategy focuses on knowledge tree construction by computing the semantic similarity between the query terms as well as the ontological entities. Furthermore, the semantic similarity is again computed between nodes of the constructed knowledge tree and URLs in the URL repository to recommend relevant webpages. The dynamic ontology alignment by computing their respective semantic similarity constitutes Ontology Semantics. Personalisation is achieved by prioritisation of webpages by content-based analysis of the users' web usage data. An overall accuracy of 87.73% is achieved by the proposed approach.
Keywords: ontologies; personalised; semantic strategy; webpage recommendation system; web search.
International Journal of Intelligent Systems Technologies and Applications, 2019 Vol.18 No.1/2, pp.115 - 132
Received: 08 Apr 2017
Accepted: 10 Jul 2017
Published online: 07 Feb 2019 *