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Subject: Computer Science (provided by Thomson Reuters)
Title:
基于MapReduce的数据挖掘平台设计与实现
Alternative Title: design and implementation of mapreduce-based data mining platform
Author: 黄斌 ; 许舒人 ; 蒲卫
Keyword: MapReduce编程模型 ; 数据挖掘 ; Hadoop平台 ; 模型驱动 ; 可视化
Source: 计算机工程与设计
Issued Date: 2013
Volume: 34, Issue:2, Pages:495-501
Indexed Type: CNKI ; WANFANG ; CSCD
Department: 中国科学院软件研究所软件工程技术中心;中国科学院研究生院;解放军卫生信息中心;
Sponsorship: 国家科技重大专项核高基基金项目(2010ZX01042-001-001-05)|国家科技支撑计划基金项目(2012BAH05F02、2011BAH15B03)
Abstract: MapReduce编程模型的简单性和高性价比使得其适用于海量数据的并行处理。然而,MapReduce欠缺对多数据源、组件复用以及数据可视化支持,这些缺点使用户在运用MapReduce框架进行数据挖掘时暴露出开发效率低下,重复开发等问题。提出了一种基于MapReduce的数据挖掘平台的设计与实现,该设计思想为Hadoop作为大规模数据计算平台在数据挖掘、数据可视化以及商业智能应用方面的不足提供了参考与弥补。同时,基于该方法实现了一个大规模数据挖掘工具。
English Abstract: Profiting from its simplicity and high cost performance, MapReduce programming paradigm is suitable for massive parallel data processing. However, MapReduce's lacking supports for multiple data source, component reuse, and data visua-lization bring in problems such as low efficiency development and redundant coding. A new design and implementation of MapReduce-based data mining platform is proposed to give reference implementation of massive data mining, data visualization and business intelligence applications based on Hadoop. Based on this proposal, a massive data mining tool is implemented.
Language: 中文
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/15545
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
黄斌,许舒人,蒲卫. 基于MapReduce的数据挖掘平台设计与实现[J]. 计算机工程与设计,2013-01-01,34(2):495-501.
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