A Context-Aware Personalized Hybrid Book Recommender System





Recommendation system, context – aware, personality, demographic, location, review sentiment, purchase reason


Contextual information such as emotion, location and time can effectively improve product or service recommendations, however, studies incorporating them are lacking. This paper presents a context-aware recommender system, personalized based on several user characteristics and product features. The recommender system which was customized to recommend books, was aptly named as a Context-Aware Personalized Hybrid Book Recommender System, which utilized users’ personality traits, demographic details, location, review sentiments and purchase reasons to generate personalized recommendations. Users’ personality traits were determined using the Ten Item Personality Inventory. The results show an improved recommendation accuracy compared to the existing algorithms, and thus indicating that the integration of several filtering techniques along with specific contextual information greatly improves recommendations.


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Author Biographies

Hossein Arabi, Bookurve Sdn. Bhd., Malaysia

Hossein Arabi received his Ph.D in information system from University of Malaya in 2018. He is currently working as a solution architect which is leading the design, development, implementation and testing of IT solutions. Over the years, he has been involved in development of variety systems, from monolithic architecture to modular-based and now on micro-service architecture.

Vimala Balakrishnan, Department of Information Systems, University of Malaya, Kuala Lumpur 50603, Malaysia

Vimala Balakrishnan is an Associate Professor and a Fulbright Research Scholar affiliated with the Faculty of Computer Science and Information Technology, University of Malaya since 2010. She obtained her PhD. in the field of Ergonomics from Multimedia University, whereas her Masters and Bachelor degrees were from University of Science Malaysia. Dr Balakrishnan’s main research interests are in data analytics and sentiment analysis, particularly related to social media. Her research domains include healthcare, education and social issues such as cyberbullying. She has published approximately 60 articles in top indexed journals and 44 conference proceedings, has four patents and eight copy-rights.

Nor Liyana Mohd Shuib, Department of Information Systems, University of Malaya, Kuala Lumpur 50603, Malaysia

Nor Liyana Mohd Shuib obtained her Master of Information System (Data Mining) from Universiti Kebangsaan Malaysia in 2005 and a Ph.D. from the University of Malaya, Malaysia in 2013 respectively. She is a Senior Lecturer at the Department of Information Systems, Faculty of Computer Science & Information Technology, University of Malaya, Malaysia. She has published a number of journal papers and proceedings locally and internationally. Her research interests include personalization, e-learning, recommender system, data science, data mining, artificial intelligence application, and educational technology. She has won more than 20 awards from reputable innovation competition internationally. She is also a Senior Member of IEEE computing society, an active blogger and presently, the principal investigator of multiple research grant in the Faculty.


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