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Research Article · Free to read · Published 4 April 2011

An Ontology Based Approach to Implement the Online Recommendation System

Vijayakumar Mohanraj & Muthaial Chandrasekaran

Journal of Computer Science, Volume 7, Issue 4, pp. 573–581 · doi.org/10.3844/jcssp.2011.573.581

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Abstract

Problem statement: Every web user has different intent when accessing the information on website. The primary goal of recommendation system is to anticipate the user intent and recommend the web pages that contain user expected information. Effective recommendation of web pages involves two important challenges: accurately identifying the user intent and predict the result show that novel web usage mining method and ontological concept scoring algorithm based on website domain ontological profile helps the recommendation system imminent navigation pattern in such a way that it provides required content while users browse the predicted navigation. Approach: We present a ontology based approach to implement recommendation system that involves applying innovative web usage mining on log system to discover all possible imminent navigation patterns of current user and resolve any uncertainties in discovering the navigation pattern by applying ontological concept based similarity comparison and scoring algorithm. Results: result show that novel web usage mining method and ontological concept scoring algorithm based on website domain ontological profile helps the recommendation system to predict and present most relevant navigation pattern to users. Conclusion: our recommendation system confirms that ontology based approach should be used to ensure excellent accuracy in predicting and capturing future navigation pattern of web user.

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Mohanraj, V. & Chandrasekaran, M. (2011). An Ontology Based Approach to Implement the Online Recommendation System. Journal of Computer Science, 7(4), 573–581. https://doi.org/10.3844/jcssp.2011.573.581

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An Ontology Based Approach to Implement the Online Recommendation SystemJournal of Computer Science · Volume 7, Issue 4 · pp. 573–581 · © Science PublicationsDownload