A Novel Rule based Data Mining Approach towards Movie Recommender System

IF 0.3 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mugdha Sharma, Laxmi Ahuja, Vinay Kumar
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引用次数: 2

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.
一种新的基于规则的电影推荐系统数据挖掘方法
所提出的研究工作是在基于规则的基于内容的群组推荐系统的帮助下,向一组用户提供准确的电影推荐。整个方法分为两个阶段。在第一阶段,提出了一种基于规则的方法,该方法考虑用户的观看历史,为每个用户提供规则库。在第二阶段,提出了一种新颖的群组推荐系统,该系统根据第一阶段生成的规则库来考虑电影的评级。阶段2还考虑组中每个单独成员的权重,以向该特定用户组提供准确的电影推荐。实验设置的结果还证实了这样一个事实,即与C4.5等其他规则学习算法相比,所提出的系统在精度和召回率方面提供了更准确的结果。
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来源期刊
Journal of Information and Organizational Sciences
Journal of Information and Organizational Sciences COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
1.10
自引率
0.00%
发文量
14
审稿时长
12 weeks
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