HyPeRM: A hybrid personality-aware recommender for movie
Recommendation systems aim to provide end users with suggestions about items, social elements, products or services that are likely to be of their interests. Most studies on recommender systems focus on finding ways to improve the recommendations, including personalizing the systems based on details...
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| Format: | Article |
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Faculty of Computer Science and Information Technology, University of Malaya
2018
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| _version_ | 1825721856715390976 |
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| author | Balakrishnan, Vimala Arabi, Hossein |
| author_facet | Balakrishnan, Vimala Arabi, Hossein |
| author_sort | Balakrishnan, Vimala |
| collection | UM |
| description | Recommendation systems aim to provide end users with suggestions about items, social elements, products or services that are likely to be of their interests. Most studies on recommender systems focus on finding ways to improve the recommendations, including personalizing the systems based on details such as demographics, location, time and emotion, among others. In this work, a hybrid recommender system, namely HyPeRM, is presented, which uses users' personality traits along with their demographic details (i.e. age and gender) to improve the overall quality of recommendations. The popular Big Five personality trait measurement scale was used to gauge users' personalities. HyPeRM was evaluated using two metrics, that is, Standardized Root Mean Square Residual (SRMR) and Root Mean Square Error of Approximation (RMSEA). Both metrics revealed that HyPeRM outperformed the baseline model (i.e. one without user's personality) in terms of the recommendation accuracies. The study shows that user recommendations can be further enhanced when their personality traits are taken into consideration, and thus their overall search experience can be improved as well. |
| first_indexed | 2024-03-06T05:56:44Z |
| format | Article |
| id | um.eprints-22360 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:56:44Z |
| publishDate | 2018 |
| publisher | Faculty of Computer Science and Information Technology, University of Malaya |
| record_format | dspace |
| spelling | um.eprints-223602019-09-13T07:58:17Z http://eprints.um.edu.my/22360/ HyPeRM: A hybrid personality-aware recommender for movie Balakrishnan, Vimala Arabi, Hossein QA75 Electronic computers. Computer science Recommendation systems aim to provide end users with suggestions about items, social elements, products or services that are likely to be of their interests. Most studies on recommender systems focus on finding ways to improve the recommendations, including personalizing the systems based on details such as demographics, location, time and emotion, among others. In this work, a hybrid recommender system, namely HyPeRM, is presented, which uses users' personality traits along with their demographic details (i.e. age and gender) to improve the overall quality of recommendations. The popular Big Five personality trait measurement scale was used to gauge users' personalities. HyPeRM was evaluated using two metrics, that is, Standardized Root Mean Square Residual (SRMR) and Root Mean Square Error of Approximation (RMSEA). Both metrics revealed that HyPeRM outperformed the baseline model (i.e. one without user's personality) in terms of the recommendation accuracies. The study shows that user recommendations can be further enhanced when their personality traits are taken into consideration, and thus their overall search experience can be improved as well. Faculty of Computer Science and Information Technology, University of Malaya 2018 Article PeerReviewed Balakrishnan, Vimala and Arabi, Hossein (2018) HyPeRM: A hybrid personality-aware recommender for movie. Malaysian Journal of Computer Science, 31 (1). pp. 48-62. ISSN 0127-9084, DOI https://doi.org/10.22452/mjcs.vol31no1.4 <https://doi.org/10.22452/mjcs.vol31no1.4>. https://doi.org/10.22452/mjcs.vol31no1.4 doi:10.22452/mjcs.vol31no1.4 |
| spellingShingle | QA75 Electronic computers. Computer science Balakrishnan, Vimala Arabi, Hossein HyPeRM: A hybrid personality-aware recommender for movie |
| title | HyPeRM: A hybrid personality-aware recommender for movie |
| title_full | HyPeRM: A hybrid personality-aware recommender for movie |
| title_fullStr | HyPeRM: A hybrid personality-aware recommender for movie |
| title_full_unstemmed | HyPeRM: A hybrid personality-aware recommender for movie |
| title_short | HyPeRM: A hybrid personality-aware recommender for movie |
| title_sort | hyperm a hybrid personality aware recommender for movie |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT balakrishnanvimala hypermahybridpersonalityawarerecommenderformovie AT arabihossein hypermahybridpersonalityawarerecommenderformovie |