Personalized recommendation engine using HADOOP

Uma Sahu, A. Tripathy, Apurva Chitnis, Karen Aubrey Corda, Sharon Rodrigues
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引用次数: 5

Abstract

More and more E-commerce Websites provide products with different prices which made it hard for consumers to find the products and services they want. In order to overcome this data overload, personalized recommendation engines are used to suggest products and to provide consumers with relevant data to help them decide which products to purchase. Recommendation engines are highly computational and hence ideal for the Hadoop Platform. This system aims at building a book recommendation engine which uses item or user based recommendation from Mahout for recommending books. It will analyze the data and give suggestions based on what similar users did and on the past transaction history of the user.
个性化推荐引擎使用HADOOP
越来越多的电子商务网站提供不同价格的产品,这使得消费者很难找到他们想要的产品和服务。为了克服这种数据过载,使用个性化推荐引擎来推荐产品,并向消费者提供相关数据,帮助他们决定购买哪些产品。推荐引擎是高度计算的,因此非常适合Hadoop平台。本系统旨在建立一个图书推荐引擎,该引擎使用Mahout基于项目或用户的推荐来推荐图书。它将分析数据,并根据类似用户的行为和用户过去的交易历史给出建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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