A Trusted User Model for Collaborative Multi-Criteria Recommendation using User Review Elements-Reference-Cited by-同舟云学术

A Trusted User Model for Collaborative Multi-Criteria Recommendation using User Review Elements

Published:2023-10-13 Issue: Volume: Page:48-53
ISSN:
Container-title:Proceedings of the 2023 7th International Conference on Advances in Artificial Intelligence
language:
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Author:

AL-Ghuribi Sumaia Mohammed¹^ORCID,Mohd Noah Shahrul Azman²^ORCID,Al Ameri Saeed Amer²^ORCID,Mohd Masnizah³^ORCID,Che Alhadi Arifah⁴^ORCID

Affiliation:

1. Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Malaysia

2. Center for Artificial Intelligence , Universiti Kebangsaan Malaysia, Malaysia

3. Center for Cyber Security, Universiti Kebangsaan Malaysia, Malaysia

4. Department of Computer Science, Universiti Malaysia Terengganu, Malaysia

Funder

Malaysia Ministry of Higher Education

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3633598.3633621

Reference23 articles.

1. Multi-Criteria Review-Based Recommender System–The State of the Art

2. Al-Ghuribi, S. M., S. A. Mohd Noah and S. Tiun, 2020. Various pre-processing strategies for domain-based sentiment analysis of unbalanced large-scale reviews. International Conference on Advanced Intelligent Systems and Informatics, Springer.

3. Integrating contextual sentiment analysis in collaborative recommender systems

4. Integration of Linked Open Data in Collaborative Group Recommender Systems

5. Caputo, A., P. Basile, M. de Gemmis, , 2017. SABRE: A Sentiment Aspect-Based Retrieval Engine. Information Filtering and Retrieval, Springer: 63-78.

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