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Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
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Data-Intensive Text Processing with MapReduce (Paperback)
Loot Price: R1,004
Discovery Miles 10 040
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Data-Intensive Text Processing with MapReduce (Paperback)
Series: Synthesis Lectures on Human Language Technologies
Expected to ship within 18 - 22 working days
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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. Table of
Contents: Introduction / MapReduce Basics / MapReduce Algorithm
Design / Inverted Indexing for Text Retrieval / Graph Algorithms /
EM Algorithms for Text Processing / Closing Remarks
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