A Novel Rule based Data Mining Approach towards Movie Recommender System

Authors

  • Mugdha Sharma Amity School of Engineering &Technology, Amity University
  • Laxmi Ahuja Amity Institute of Information Technology, Amity University
  • Vinay Kumar Vivekananda Institute of Professional Studies, Guru Gobind Singh Indraprastha University

DOI:

https://doi.org/10.31341/jios.44.1.7

Keywords:

Data Mining, Movie Recommender System, Group Preferences, MovieLens, Classification Rules, Rule Base

Abstract

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.

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Published

2020-06-24

How to Cite

[1]
M. Sharma, L. Ahuja, and V. Kumar, “A Novel Rule based Data Mining Approach towards Movie Recommender System”, J. inf. organ. sci. (Online), vol. 44, no. 1, Jun. 2020.

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Section

Articles