A context-aware personalized hybrid book recommender system
Document Type
Article
Publication Date
1-1-2020
Abstract
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.
Keywords
Recommendation system, Context-aware, Personality, Demographic, Location, Review sentiment, Purchase reason
Divisions
infosystem
Funders
None
Publication Title
Journal of Web Engineering
Volume
19
Issue
3-4
Publisher
River Publishers
Publisher Location
ALSBJERGVEJ 10, GISTRUP, 9260, DENMARK