Open AccessA Novel Rule based Data Mining Approach towards Movie Recommender System
Author(s) -
Mugdha Sharma,
Laxmi Ahuja,
Vinay Kumar
Publication year - 2020
Publication title -
journal of information and organizational sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.146
H-Index - 13
eISSN - 1846-9418
pISSN - 1846-3312
DOI - 10.31341/jios.44.1.7
Subject(s) - recommender system , computer science , recall , base (topology) , rule based system , precision and recall , group (periodic table) , information retrieval , data mining , artificial intelligence , machine learning , mathematics , psychology , mathematical analysis , chemistry , organic chemistry , cognitive psychology
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.