Collaborative and content based filtering personalized recommender system for book / Hossein Arabi
Personalized recommendation systems provide end users with suggestions about information items, social elements, products or services that are likely to be of their interest based on users' details such as demographics, location, time, and emotion. Incorporating contextual information in rec...
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| Format: | Thesis |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/8978/1/Hossein.pdf http://studentsrepo.um.edu.my/8978/6/hossein.pdf http://studentsrepo.um.edu.my/8978/ |
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| _version_ | 1831435225774686208 |
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| author | Hossein, Arabi |
| author_facet | Hossein, Arabi |
| author_sort | Hossein, Arabi |
| building | UM Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaya |
| content_source | UM Student Repository |
| continent | Asia |
| country | Malaysia |
| description | Personalized recommendation systems provide end users with suggestions about
information items, social elements, products or services that are likely to be of their
interest based on users' details such as demographics, location, time, and emotion.
Incorporating contextual information in recommendation system is an effective
approach to create more accurate and personalized recommendations. Therefore, in this
study, a Personalized Hybrid Book Recommender is proposed, which integrates several
users’ characteristics, namely their personality traits, demographic details and current
location, together with review sentiments and purchase reason, to improve their book
recommendations. The system is able to determine user’s personality traits by utilizing
the Ten Item Personality Inventory. The proposed recommender system would be
evaluated using two metrics, that are, Standardized Root Mean Square Residual and
Root Mean Square Error of Approximation. The proposed technique was evaluated by
comparing it against baseline models and existing personalized recommendation
systems. This study is able to show effectiveness of integrating user’s contextual data
(personality trait, demographic data and location) with product’s features (review and
purchase reason). |
| format | Thesis |
| id | my.um.stud-8978 |
| institution | Universiti Malaya |
| publishDate | 2018 |
| record_format | eprints |
| spelling | my.um.stud-89782021-02-16T19:19:23Z Collaborative and content based filtering personalized recommender system for book / Hossein Arabi Hossein, Arabi QA75 Electronic computers. Computer science Personalized recommendation systems provide end users with suggestions about information items, social elements, products or services that are likely to be of their interest based on users' details such as demographics, location, time, and emotion. Incorporating contextual information in recommendation system is an effective approach to create more accurate and personalized recommendations. Therefore, in this study, a Personalized Hybrid Book Recommender is proposed, which integrates several users’ characteristics, namely their personality traits, demographic details and current location, together with review sentiments and purchase reason, to improve their book recommendations. The system is able to determine user’s personality traits by utilizing the Ten Item Personality Inventory. The proposed recommender system would be evaluated using two metrics, that are, Standardized Root Mean Square Residual and Root Mean Square Error of Approximation. The proposed technique was evaluated by comparing it against baseline models and existing personalized recommendation systems. This study is able to show effectiveness of integrating user’s contextual data (personality trait, demographic data and location) with product’s features (review and purchase reason). 2018-07 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/8978/1/Hossein.pdf application/pdf http://studentsrepo.um.edu.my/8978/6/hossein.pdf Hossein, Arabi (2018) Collaborative and content based filtering personalized recommender system for book / Hossein Arabi. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/8978/ |
| spellingShingle | QA75 Electronic computers. Computer science Hossein, Arabi Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title | Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title_full | Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title_fullStr | Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title_full_unstemmed | Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title_short | Collaborative and content based filtering personalized recommender system for book / Hossein Arabi |
| title_sort | collaborative and content based filtering personalized recommender system for book / hossein arabi |
| topic | QA75 Electronic computers. Computer science |
| url | http://studentsrepo.um.edu.my/8978/1/Hossein.pdf http://studentsrepo.um.edu.my/8978/6/hossein.pdf http://studentsrepo.um.edu.my/8978/ |
| url_provider | http://studentsrepo.um.edu.my/ |