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Customization of Recommendation System Using Collaborative Filtering Algorithm on Cloud Using Mahout

机译:使用MAHOUT在云上使用协同过滤算法的推荐系统定制

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Recommendation System helps people in decision making regarding an item/person. Growth of World Wide Web and E-commerce are the catalyst for recommendation system. Due to large size of data, recommendation system suffers from scalability problem. Hadoop is one of the solutions for this problem. Collaborative filtering is a machine learning algorithm and Mahout is an open source java library which favors collaborative filtering on Hadoop environment. The paper discusses on how recommendation system using collaborative filtering is possible using Mahout environment. The performance of the approach has been presented using Speedup and efficiency.
机译:推荐系统有助于人们关于项目/人员的决策。万维网和电子商务的增长是推荐系统的催化剂。由于数据大小的数据,推荐系统遭受可扩展性问题。 Hadoop是这个问题的解决方案之一。协作过滤是一种机器学习算法,MAHOUT是一个开源Java库,其利用Hadoop环境的协作过滤。本文讨论了如何使用Mahout环境使用协作滤波的推荐系统。采用加速和效率呈现了该方法的性能。

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