Hybrid Recommender System with Conceptualization and Temporal Preferences

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)


From the last couple of decades, the web services on the Internet changed the perspectives of the usage of a normal user as well as the vendor. Recommender systems are the intelligent agents that provide suggestions regarding the navigation in the web site for a user, based on preferences mentioned by the user in the past usage. Although there were several hybrid recommenders available with content-based and collaborative strategies, they were unable to process semantics about temporal and conceptual aspects. This paper incorporates the domain knowledge of the web site and the semantics for the temporal constructs into the hybrid recommender system. The proposed recommender parse the personalized ontology constructed for a user based on temporal navigation patterns and suggests the pages. The effectiveness of this approach is demonstrated by the experiments varying the scale of the data set and analyzed with the user’s satisfaction toward the quality of recommendations.


Hybrid recommender system Ontology Usage patterns Temporal concepts 


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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Chaitanya Bharathi Institute of TechnologyHyderabadIndia
  2. 2.Jawaharlal Nehru Technological University Hyderabad College of EngineeringKarimnagarIndia

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