文章基本信息

标题：A Hybrid Recommender System for Performance Improvement using Personal Propensity
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作者：Dr. Amit Verma ; Harpreet Kaur Virk
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2015
卷号：6
期号：3
页码：122-126
语种：English
出版社：Ayushmaan Technologies
摘要：Recommendations basically are the suggestions that one experience in day to day life. Actually we all depend on suggestions from others to do our daily work for example choosing dress to wear we ask others for suggestions. In selection process such as filtering, the systems select items previously chosen by the actual or true user, whereas in collaborative filtering or selection , recommendations are based on the data or entity of similar users or items. The recommendations are also influenced by the various factors such as age, gender and some other user profile information. In this paper, Hybrid Recommender System for Performance Improvement using Personal Propensity is presented . The Mutate and standard deviation are the key component used in this paper. The system is evaluated using various parameter like precision and recall.
关键词：Recommender System;Filtering;Precision;Recall etc