Arabi, Hossein and Balakrishnan, Vimala and Mohd Shuib, Nor Liyana (2020) A context-aware personalized hybrid book recommender system. Journal of Web Engineering, 19 (3-4). pp. 405-427. ISSN 15409589, DOI https://doi.org/10.13052/jwe1540-9589.19343.
Full text not available from this repository.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.
| Item Type: | Article |
|---|---|
| Funders: | None |
| Uncontrolled Keywords: | Recommendation system; Context-aware; Personality; Demographic; Location; Review sentiment; Purchase reason |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Information System |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 08 Nov 2024 01:45 |
| Last Modified: | 08 Nov 2024 01:45 |
| URI: | http://eprints.um.edu.my/id/eprint/36981 |
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