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This book presents a practical, implementation-oriented introduction to processing massive text datasets using the MapReduce programming model, especially for natural-language processing (NLP) and information-retrieval tasks. It covers MapReduce program design, distributed data processing, and shows how classical NLP tasks (e.g. word counts, indexing, statistical language modeling) can be scaled to large datasets. The goal is to enable researchers and engineers to build scalable, data-intensive text-processing systems using the MapReduce paradigm on distributed platforms.

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245: $a: Data-Intensive Text Processing with MapReduce
245: $b:
082: $a:
100: $a: Jimmy Lin & Chris Dyer
650: $a: Large-scale text processing
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440: $v:
250: $b: Morgan & Claypool Publishers
250: $c: 2010
020: $a: 978-1-60845-342-9
300: $a: 252