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《MapReduce进行密集文本数据处理》(Data-Intensive Text Processing with MapReduce)文字版[PDF]

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  • 摘要:
    图书分类软件
    出版社SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES
    发行时间2010年
    语言英文
  • 时间: 2011/11/29 21:11:01 发布 | 2011/11/30 20:34:03 更新
  • 分类: 图书  计算机与网络 

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中文名MapReduce进行密集文本数据处理
原名Data-Intensive Text Processing with MapReduce
图书分类软件
资源格式PDF
版本文字版
出版社SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES
书号9781608453436
发行时间2010年
地区美国
语言英文
简介

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内容介绍:

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. 

内容截图 

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目录

1.Introduction
2.MapReduce Basics
3.MapReduce algorithm design
4.Inverted Indexing for Text Retrieval
5.Graph Algorithms
6.EM Algorithms for Text Processing
7.Closing Remarks

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