A Comprehensive Survey on Comparisons across Contextual Pre-filtering, Contextual Post-filtering and Contextual Modelling Approaches

Khalid Haruna (University of Malaya Bayero University, Malaysia)
Maizatul Akmar Ismail (University of Malaya, Malaysia)
Damiasih Damiasih (Sekolah Tinggi Pariwisata Ambarrukmo, Indonesia)
Haruna Chiroma (Federal College of Education (Technical) Gombe, Nigeria)
Tutut Herawan (Politeknik Negeri Malang Sekolah Tinggi Pariwisata Ambarrukmo Universitas Teknologi Yogyakarta, Indonesia)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 15, No 4: December 2017

Recently, there has been growing interest in recommender systems (RS) and particularly in context-aware RS. Methods for generating context-aware recommendations are classified into pre-filtering, post-filtering and contextual modelling approaches. In this paper, we present the several novel approaches of the different variant of each of these three contextualization paradigms and present a complete survey on the state-of-the-art comparisons across them. We then identify the significant challenges that require being addressed by the current RS researchers, which will help academicians and practitioners in comparing these three approaches to select the best alternative according to their strategies.