A Multi-Criteria Collaborative Filtering Approach Using Deep Learning and Dempster-Shafer Theory for Hotel Recommendations
نویسندگان
چکیده
This paper addresses the problem of multi-criteria recommendation in hotel industry. The main focus is to analyze user preferences from different aspects based on ratings and develop a new collaborative filtering method for recommendations. Particularly, proposed system integrates matrix factorization into deep learning model predict ratings, then evidential reasoning approach adopted uncertainty those represented as mass functions Dempster-Shafer theory evidence. Finally, Dempster’s rule combination utilized aggregate obtain overall rating recommendation. Extensive experiments conducted real-world dataset demonstrate effectiveness efficiency compared with other methods.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3165310