A Novel Rule based Data Mining Approach towards Movie Recommender System

Autor: Mugdha Sharma, Laxmi Ahuja, Vinay Kumar
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Information and Organizational Sciences, Vol 44, Iss 1, Pp 157-170 (2020)
Druh dokumentu: article
ISSN: 1846-3312
1846-9418
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: Directory of Open Access Journals