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29 Free eBooks On Databases, Data Mining And Information Retrieval
 
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29 Free eBooks On Databases, Data Mining And Information Retrieval  
 
Here we bring to you 29 ebooks on Databases, Data Mining and Information Retrieval absolutely free! Read, explore and share.   
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Saturday, October 26, 2013 Information Retrieval, Databases and data mining are the current in thing in the IT world! Learn more about the subject with these 29 absolutely free ebooks for online reading and downloading. Happy reading!

free ebooks, free ebooks technology, Databases, Data Mining, Information Retrieval, Free ebooks on Databases, Free ebooks on Data Mining, Free ebooks on  Information Retrieval




1. Theory and Applications for Advanced Text Mining
by Shigeaki Sakurai (ed.) - InTech , 2012
Text mining techniques are studied aggressively in order to extract the knowledge from the data. This book introduces advanced text mining techniques. There are various techniques from relation extraction to under or less resourced language.

2. Foundations of Databases
by Serge Abiteboul, Richard Hull, Victor Vianu - Addison Wesley , 1994
This book provides in-depth coverage of the theory concerning the logical level of database management systems, including both classical and advanced topics. It includes detailed proofs and numerous examples and exercises.

3. Internet Advertising
by S. Yuan, A.Z. Abidin, M. Sloan, J. Wang - arXiv , 2012
A comprehensive survey on Internet advertising, discussing the research issues, identifying the recent technologies, and suggesting its future directions. We start with a brief history, introduction, and classification of the industry.

4. The Theory of Relational Databases
by David Maier - Computer Science Press , 1983
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...

5. Data-Intensive Text Processing with MapReduce
by Jimmy Lin, Chris Dyer - Morgan & Claypool Publishers , 2010
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.

6. Data Mining Algorithms In R
- Wikibooks , 2010
Data mining comprises techniques and algorithms, for determining interesting patterns from large datasets. There are currently hundreds algorithms that perform tasks such as frequent pattern mining, clustering, and classification, among others.

7. An Introduction to Data Mining
by Saed Sayad - University of Toronto , 2011
Data Mining is about explaining the past and predicting the future by means of data analysis. Data mining is a multidisciplinary field which combines statistics, machine learning, artificial intelligence and database technology.

8. Mining of Massive Datasets
by Anand Rajaraman, Jeffrey D. Ullman - Stanford University , 2010
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.

9. Information Retrieval: A Survey
by Ed Greengrass - University of Maryland , 2000
This is a survey of the state of the art in the dynamic field of information retrieval. Topics covered include: formulation of queries and topic statements, indexing of document collections, methods for computing the similarity of documents, etc.

10. Database Fundamentals
by Neeraj Sharma, at al. - IBM Corporation , 2010
This free e-book teaches you the fundamentals of databases, including relational database theory, logical and physical database design, and the SQL language. Advanced topics include using functions, stored procedures and XML.

11. Multi-Relational Data Mining
by Arno Jan Knobbe - IOS Press , 2006
This thesis is concerned with Data Mining: extracting useful insights from large collections of data. With the increased possibilities in modern society for companies and institutions to gather data, this subject has become of increasing importance.

12. Natural Language Interfaces to Databases: An Introduction
by I. Androutsopoulos, G. D. Ritchie, P. Thanisch - arXiv , 1995
This paper is an introduction to natural language interfaces to databases (NLIDBs). Some advantages and disadvantages of NLIDBs are then discussed, comparing NLIDBs to formal query languages, form-based interfaces, and graphical interfaces.

13. Readings in Database Systems
by J. M. Hellerstein, M. Stonebraker - UC Berkeley , 1999
These lecture notes provide students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area.

14. Database Systems and Structures
by Osmar R. Zaiane - Simon Fraser University , 1998
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.

15. Data Mining Desktop Survival Guide
by Graham Williams - Togaware Pty Ltd , 2004
Data mining is about building models from data. We build models to gain insights into the world and how the world works. A data miner, in building models, deploys many different data analysis and model building techniques.

16. Introduction to Metadata
by Tony Gill, at al. - Getty Publications , 2008
This book provides an overview of metadata, its types, roles, and characteristics; a discussion of metadata as it relates to resources on the Web; a description of methods, tools, standards, and protocols used to publish digital collections; etc.

17. Database design with UML and SQL
by Tom Jewett , 2006
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.

18. The Relational Model for Database Management
by E. F. Codd - Addison-Wesley , 1990
Written by the originator of the relational model, the book covers the practical aspects of the design of relational databases. The author defines twelve rules that database management systems need to follow in order to be described as relational.

19. An Introduction to Relational Database Theory
by Hugh Darwen - BookBoon , 2009
This book introduces the theory of relational databases, focusing on the application of that theory to the design of computer languages that properly embrace it. The book covers different topics: Types, Variables, Operators, Relational Algebra, etc.

20. XML and Databases
by Ronald Bourret , 2005
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.

21. Data Mining in Medical and Biological Research
by Eugenia G. Giannopoulou - InTech , 2008
This book brings together the most recent advances of data mining research in the promising areas of medicine and biology. It consists of seventeen chapters which describe interesting applications, motivating progress and worthwhile results.

22. Data Mining and Knowledge Discovery in Real Life Applications
by Julio Ponce, Adem Karahoca - InTech , 2009
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.

23. Storage Basics: An Introduction to the Fundamentals of Storage Technology
- Fujitsu Siemens Computers , 2009
This book is an introduction to storage technologies and storage networks. It also provides an overview of the storage product portfolio of Fujitsu Siemens Computers which is the basis for solutions that help you manage the growing flood of data.

24. Data Modeling Techniques for Data Warehousing
by Chuck Ballard, et al. - IBM Redbooks , 1998
It covers data modeling techniques for data warehousing, within the context of the overall data warehouse development process. The process of data warehouse modeling, including the steps required before and after the actual modeling, is discussed.

25. Information Retrieval
by C. J. van Rijsbergen - Butterworth-Heinemann , 1979
The material of this book is aimed at advanced undergraduate information or computer science students, postgraduate library science students, and research workers in the field of IR. There is a new chapter on probabilistic retrieval.

26. Forensic Analysis of Database Tampering
by Kyriacos E. Pavlou, Richard T. Snodgrass - University of Arizona , 2008
The text on detection via cryptographic hashing. The authors show how to determine when the tampering occurred, what data was tampered, and who did the tampering. Four successively more sophisticated forensic analysis algorithms are presented.

27. Concurrency Control and Recovery in Database Systems
by P. A. Bernstein, V. Hadzilacos, N. Goodman - Addison Wesley , 1987
This book is about techniques for concurrency control and recovery. It covers techniques for centralized and distributed computer systems, and for single copy, multiversion, and replicated databases. Example applications are included.

28. Information Retrieval Interaction
by Peter Ingwersen - Taylor Graham Publishing , 2002
The book establishes a unifying scientific approach to IR – a synthesis based on the concept of IR interaction and the Cognitive Viewpoint. It present research and developments in the field of information retrieval based on a new categorisation.

29. Introduction to Information Retrieval
by Manning, Raghavan, Schütze - Cambridge University Press , 2008
This textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It is written from a computer science perspective by three leading experts in the field.

Atithya Amaresh, EFYTIMES News Network


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