文章基本信息

标题：Discovering User-Item Subgroup and Predicting Domain-Specific Correlations in Recommendation Approaches by Using DsRec Algorithm
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作者：sunitha Vanamala ; Umarani ; myakala Gouthami 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：8
页码：17214
DOI：10.15680/IJIRSET.2017.0608224
出版社：S&S Publications
摘要：with the wide kind of services and products to be had at the internet, it is hard for users to pick out theproduct or service that maximum meets their wishes. In order to reduce or maybe put off this issue, recommendersystems have emerged. A recommender system is used in diverse fields to suggest items of interest to users. One of themain regions where this concept is currently used is e-commerce that interacts immediately with customers bysuggesting products of interest with the intention of enhancing its income. Motivated via the remark, a novel DomainsensitiveRecommendation (DsRec) set of rules is proposed, to make the rating prediction by using exploring the useritemsubgroup evaluation concurrently, in which a consumer-item subgroup is deemed as a website together with asubset of items with comparable attributes and a subset of customers who have pastimes in these objects. CollaborativeFiltering (CF) is an effective and widely adopted recommendation approach. Different from content material-primarilybased recommender structures which rely on the profiles of customers and gadgets for predictions, CF approachesmake predictions by using most effective utilizing the user-item interaction records consisting of transaction history orobject pride expressed in scores, etc.