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A Hybrid Recommendation Approach for Personalized Retrieval of Research Articles

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  • Olatunji Mumini Omisore

    (Centre for Information Technology and System, University of Lagos, Lagos, Nigeria)

Abstract

Trends of researches in information filtering has advanced the use of Recommender Systems (RSs) in many E-business sites, and re-shaped their commercial activities. Recommendations made by such systems are casted within an informal community of users and social context. As a result, a number of RS techniques have been proposed. Single and hybrid RSs have been applied to enhance recommendation. In this study, a hybrid recommendation approach for personalized retrieval of research articles was propose to improve researchers' accuracy in research article retrieval. Collaborative, Context-Based, and Knowledge Based filtering approaches of RS are integrated. Results obtained from the filters are amalgamated with an averaging technique to produce optimal result from which top-N are recommended to researchers. Evaluation of results obtained from experimental study shows the model was able to recommend articles with notable precise relevance.

Suggested Citation

  • Olatunji Mumini Omisore, 2014. "A Hybrid Recommendation Approach for Personalized Retrieval of Research Articles," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 4(4), pages 42-60, October.
    • Handle: RePEc:igg:jirr00:v:4:y:2014:i:4:p:42-60
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