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 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 Shigeaki Sakurai (ed.) - InTech
Text mining techniques are studied aggressively in order to extract the knowledge from the data. This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
by Ronald Bourret
This paper gives a high-level overview of how to use XML with databases. It describes how the differences between data-centric and document-centric documents affect their usage with databases and how XML is commonly used with relational databases.
by David Maier - Computer Science Press
The book is intended for a second course in databases and a reference for researchers in the field. The material covered includes relational algebra, functional dependencies, multivalued and join dependencies, normal forms, representation theory...