The Research and Application of Purchase Amount Based User-KNN Algorithm on Cloud Platform in Coal Sales System

Wu Hua-qin, Shao Hua
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引用次数: 1

Abstract

With the highly development of internet e-commerce, coal shopping on-line is becoming a popular trend. With the increase of purchase data, every big coal industries hope to recommend the products which the customers will be interested with through analyzing the purchase history data. In coal system, purchase data based near neighbor algorithm is applied widely. However, with the increasing of huge big scale consuming records, traditional algorithm could complete recommendation work real-time and effectively. In this paper, focusing on huge scale coal consuming records, we propose cloud platform based user neighbor algorithm, and this algorithm is based on MapReduce distribute framework. It can complete the recommendation work distributed. Through the experimental results, we prove that the algorithm we propose has good efficiency and high scalability.
基于用户knn算法的云平台购货量在煤炭销售系统中的研究与应用
随着互联网电子商务的高度发展,网上购煤已成为一种流行趋势。随着采购数据的增加,各大煤炭企业都希望通过对采购历史数据的分析,向客户推荐自己感兴趣的产品。在煤炭系统中,基于近邻的购煤数据算法得到了广泛的应用。然而,随着海量消费记录的增加,传统算法已经无法实时有效地完成推荐工作。本文针对大规模煤耗记录,提出了基于云平台的用户邻居算法,该算法基于MapReduce分布式框架。可以完成分布式推荐工作。实验结果表明,本文提出的算法具有良好的效率和较高的可扩展性。
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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