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 retrieval, and machine learning.
Tag(s): Big Data Machine Learning
Publication date: 30 Apr 2010
ISBN-10: 1608453421
ISBN-13: 9781608453429
Paperback: 178 pages
Views: 8,543
Data-Intensive Text Processing with MapReduce
About The Author(s)
Chris Dyer is an Assistant Professor in Language Technologies Institute, Machine Learning Department (affiliated faculty), School of Computer Science at Carnegie Mellon University. His research interests lie at or near the intersection of machine learning, natural language processing, and linguistics, with multilinguality as the unifying theme of most of his works.
Chris Dyer is an Assistant Professor in Language Technologies Institute, Machine Learning Department (affiliated faculty), School of Computer Science at Carnegie Mellon University. His research interests lie at or near the intersection of machine learning, natural language processing, and linguistics, with multilinguality as the unifying theme of most of his works.
Jimmy Lin is a professor in the iSchool with joint appointments in the Department of Computer Science and UMIACS at the University of Maryland. He is also a member of both the Computational Linguistics and Information Processing Lab (CLIP) and the Human-Computer Interaction Lab (HCIL).
Jimmy Lin is a professor in the iSchool with joint appointments in the Department of Computer Science and UMIACS at the University of Maryland. He is also a member of both the Computational Linguistics and Information Processing Lab (CLIP) and the Human-Computer Interaction Lab (HCIL).