Authors: Namita Mittal; Richi Nayak; Mahesh Chandra Govil; Kamal Chand Jain
Addresses: Department of Computer Engineering, Malaviya National Institute of Technology Jaipur, JLN Marg, Jaipur 302017, Rajasthan, India ' School of Information System, Queensland University of Technology, Brisbane, QLD 4000, Australia ' Department of Computer Engineering, Malaviya National Institute of Technology Jaipur, JLN Marg, Jaipur 302017, Rajasthan, India ' Department of Mathematics, Malaviya National Institute of Technology Jaipur, JLN Marg, Jaipur 302017, Rajasthan, India
Abstract: Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.
Keywords: web information retrieval; ontology; personalisation; user profiles; collaborative filtering; clustering; recommender systems; personalised search; web recommendation.
International Journal of Knowledge and Web Intelligence, 2011 Vol.2 No.2/3, pp.119 - 137
Available online: 09 Dec 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article