A Novel Rule based Data Mining Approach towards Movie Recommender System
| Autor: | Vinay Kumar, Laxmi Ahuja, Mugdha Sharma |
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| Rok vydání: | 2020 |
| Předmět: |
Classification Rules
Group Preferences Information theory Computer science Data Mining Movie Recommender System MovieLens Rule Base Rule-based system Library and Information Sciences Recommender system computer.software_genre Computer Science Applications Data mining Q350-390 computer Information Systems |
| Zdroj: | Journal of Information and Organizational Sciences Volume 44 Issue 1 Journal of Information and Organizational Sciences, Vol 44, Iss 1, Pp 157-170 (2020) |
| ISSN: | 1846-9418 1846-3312 |
| DOI: | 10.31341/jios.44.1.7 |
| Popis: | The proposed research work is an effort to provide accurate movie recommendations to a group of users with the help of a rule-based content-based group recommender system. The whole approach is categorized into 2 phases. In phase 1, a rule- based approach has been proposed which considers the users’ viewing history to provide the Rule Base for every individual user. In phase 2, a novel group recommendation system has been proposed which considers the ratings of the movies as per the rule base generated in phase 1. Phase 2 also considers the weightage of every individual member of the group to provide the accurate movie recommendation to that particular group of users. The results of experimental setup also establish the fact that the proposed system provides more accurate outcomes in terms of precision and recall over other rule learning algorithms such as C4.5. |
| Databáze: | OpenAIRE |
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