Autor: |
Quang-Hung Le, Toan Nguyen Mau, Roengchai Tansuchat, Van-Nam Huynh |
Jazyk: |
angličtina |
Rok vydání: |
2022 |
Předmět: |
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Zdroj: |
IEEE Access, Vol 10, Pp 37281-37293 (2022) |
Druh dokumentu: |
article |
ISSN: |
2169-3536 |
DOI: |
10.1109/ACCESS.2022.3165310 |
Popis: |
This paper addresses the problem of multi-criteria recommendation in the hotel industry. The main focus is to analyze user preferences from different aspects based on multi-criteria ratings and develop a new multi-criteria collaborative filtering method for hotel recommendations. Particularly, the proposed recommendation system integrates matrix factorization into a deep learning model to predict the multi-criteria ratings, and then the evidential reasoning approach is adopted to model the uncertainty of those ratings represented as mass functions in Dempster-Shafer theory of evidence. Finally, Dempster’s rule of combination is utilized to aggregate those multi-criteria ratings to obtain the overall rating for recommendation. Extensive experiments conducted on a real-world dataset demonstrate the effectiveness and efficiency of the proposed method compared with other multi-criteria collaborative filtering methods. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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