A Hybrid Recommendation Approach for Personalized Retrieval of Research Articles
Olatunji Mumini Omisore · International Journal of Information Retrieval Research · 2014
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.