Data-Intensive Text Processing with MapReduce


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We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains.

Cluster Computing and MapReduce Lecture 1

This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Customers who bought this product also purchased.

The 32nd Annual ACM SIGIR Conference             July 19-23 2009

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Data-Intensive Text Processing with MapReduce

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.

[Corpora-List] New book: Lin & Dyer: Data-Intensive Text Processing with MapReduce

This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Jimmy Lin and Chris Dyer.


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University of Maryland, College Park. 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. Jimmy Lin and Chris Dyer claypool. Synthesis Lectures on Human Language Technologies.

Data Intensive Text Processing With Mapreduce

This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information. Book Reviews.

University of Maryland. This half-day tutorial introduces participants to data-intensive text processing with the MapReduce programming model [1], using the open-source Hadoop. Abstract: Our world is being revolutionized by data-driven methods: access to large amounts of data has.


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Data-Intensive Text Processing with Mapreduce has 32 ratings and 4 reviews. Kai said: This is a very concise text on the given topic: In the first half i. Mining of Massive Datasets. Anthology: J; Volume: Computational Linguistics.

Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce Data-Intensive Text Processing with MapReduce

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