Survey on Recommendation System
Survey on Recommendation System
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DOI：
10.5120/ijca2016908821
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发表时间：
2016-03
期刊：
影响因子：
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通讯作者：
Lipi Shah;Hetal Gaudani;Prem Balani
中科院分区：
文献类型：
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作者：
Lipi Shah;Hetal Gaudani;Prem Balani
本文介绍了推荐系统的概况。推荐系统是数据挖掘领域的一个分支。这是电子商务的时代。推荐系统用于帮助企业实施一对一的营销策略。这些类型的策略提供了几个优势，如建立客户忠诚度，增加交叉销售的可能性，通过展示客户感兴趣的项目或产品来满足客户需求。推荐系统（RS）在许多网络应用中起着至关重要的作用。推荐系统主要分为以下三类：基于内容的推荐、基于协作的推荐和混合推荐。不同的类别有其自身的优点和缺点。本文描述了每个类别的不同技术以及每个类别中的问题。
This paper describes the overview of recommendation system. The recommendation system is the sub-part of the data mining field. This is the era of the e-commerce business. Recommender systems are used to assists the enterprise to implement one-to-one marketing strategies. These type of strategies offer several advantages like establishing the customer loyalty, increase the probability of cross-selling, fulfilling the customer need by presenting the items or products of customer interest. The recommendation system (RS) is crucial in many applications on the web. The recommendation system is mainly classified into following three categories: content-based, collaborative-based and hybrid approaches. Different categories have its own advantages as well as disadvantages .This paper describes the different techniques in each category and the issues in each category.