基于Hadoop与Mahout云数据挖掘推荐研究  

Research on Cloud Data Mining Recommend Based on Hadoop and Mahout

作　　者：张赢宇 邓立国[1] 

机构地区：[1]沈阳师范大学教育技术学院,沈阳110034

出　　处：《现代计算机》2016年第1期46-48,53,共4页Modern Computer

基　　金：潍坊教育学院青年计划(No.201102js)

摘　　要：随着社会信息化时代的到来,数据成为IT领域发展最重要的决定性因素。任何事都必须用数据来说话。大数据浪潮汹涌来袭。将海量的数据资源存储在云端,形成整合统一便于管理的云数据,从而方便用户高效、精确地获取使用信息。云数据的核心并不在于数据量的大小,而是我们能否成功挖掘出云数据的价值。因此,提出一种基于Hadoop和Mahout的云数据挖掘推荐研究。通过并行化的架构和并行化的算法,处理并分析庞大的数据集,解决传统数据管理无法对云端数据进行深度挖掘的问题,让云数据转化成真正对用户有价值的信息和知识,并使其在特定的领域得以实现和验证。With the advent of social informatization, the data become the most important decisive factor in IT field. Everything must use numbers to talk. Big data wave comes. To store vast amounts of data resources in the cloud, forming manageable cloud data, thus it is easy to efficient and accurate use information. The core of the cloud data is not the size of the amount of data, but whether we can succeed to dig value of cloud data. Therefore, proposes a cloud based on Hadoop and Mahout recommended data mining research. Through parallel architecture and parallel algorithm, it processes and analyzes large data sets, solves the traditional data management on the depth of the cloud data mining problems, which lets cloud data translate into a truly valuable information and knowledge to the customer, and makes it imple-mented and validated in a particular area.

关 键 词：云数据 HADOOP Mahout 数据挖掘 推荐策略 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]