Data-Intensive Text Processing with MapReduce
by Jimmy Lin, Chris Dyer
Publisher: Morgan & Claypool Publishers 2010
Number of pages: 175
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.
Home page url
Download or read it online for free here:
by Paris C. Kanellakis - Brown University Providence
The goal of this paper is to provide a systematic and unifying introduction to relational database theory, including some of the recent developments in database logic programming. The exposition closes with the problems of complex objects...
by Tom Jewett
This text is a teaching resource for an introductory database class at California State University Long Beach, Department of Computer Engineering and Computer Science. It is also designed to be used as an individual self-study tutorial.
by Osmar R. Zaiane - Simon Fraser University
An introduction to data models, database systems, the structure and use of relational database systems and relational languages, indexing and storage management, query processing in relational databases, and the theory of relational database design.
by Julio Ponce, Adem Karahoca - InTech
This book presents different ways of theoretical and practical advances and applications of data mining in different promising areas. The book will serve as a Data Mining bible to show a right way for the students, researchers and practitioners.