e-books in Databases & Information Retrieval category
- National Academies Press , 2017
Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products.
by C.J. Date, Hugh Darwen - Addison Wesley , 2014
This is a book on database management based on an earlier book by the same authors. It can be seen as an abstract blueprint for the design of a DBMS and the language interface to such a DBMS. It serves as a basis for a model of type inheritance.
by C.J. Date, Hugh Darwen , 2013
The database field is full of important problems still to be solved and interesting issues still to be examined -- and some of those problems and issues are explored in this book. It reports on some of our most recent investigations in this field.
by Clinton Gormley, Zachary Tong - O'Reilly , 2015
Whether you need full-text search or real-time analytics of data, this book introduces you to the fundamental concepts required to start working with Elasticsearch. With these foundations laid, it will move on to more-advanced search techniques.
by Mohammed J. Zaki, Wagner Meira, Jr. - Cambridge University Press , 2014
This textbook provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification.
by Christian S. Jensen - Aalborg University , 2000
Topics covered: the semantics of temporal data, the design of data models and languages for temporal data, the design of databases expressed in terms of temporal data models as well as temporally enhanced design of conventional databases.
by Ron Zacharski - GuideToDatamining.com , 2014
Before you is a tool for learning basic data mining techniques. If you are a programmer interested in learning a bit about data mining you might be interested in a beginner's hands-on guide as a first step. That's what this book provides.
by Paris C. Kanellakis - Brown University Providence , 1989
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 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. They are various techniques from relation extraction to under or less resourced language.
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.
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.
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...
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.
- 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
- 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.
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.
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.
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.