DATA Mining - E books

محب الله ورسوله · #1 (**permalink**) 07-10-2006, 05:23 AM

DATA Mining - ebook Collected here

محب الله ورسوله · #2 (**permalink**) 07-10-2006, 05:24 AM

كود:

Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library) (Hardcover)
Product Details
Hardcover: 273 pages
Publisher: Artech House Publishers (August 1997)
Language: English
ISBN: 0890069522

Investigative Data Mining for Security and Criminal Detection
Paperback: 272 pages
Publisher: Butterworth-Heinemann; 1 edition (January 31, 2003)
Language: English
ISBN: 0750676132

Mining Your Own Business in Retail Using DB2 Intelligent Miner for Data
Paperback: 208 pages
Publisher: Ibm (August 2001)
Language: English
ISBN: 0738422940

Data Mining: A Heuristic Approach
Hardcover: 310 pages
Publisher: Idea Group Publishing (February 2002)
Language: English
ISBN: 1930708254

Data Mining: Opportunities and Challenges
Paperback: 326 pages
Publisher: Irm Press (September 28, 2003)
Language: English
ISBN: 1931777837

Intelligent Agents for Data Mining and Information Retrieval 
Hardcover: 350 pages
Publisher: Idea Group Publishing (February 2004)
Language: English
ISBN: 1591401941


Data Mining: Concepts, Models, Methods, and Algorithms 
Paperback: 360 pages
Publisher: Wiley-IEEE Press (October 25, 2002)
Language: English
ISBN: 0471228524

Data Mining Methods and Models
Hardcover: 344 pages
Publisher: Wiley-IEEE Press (January 30, 2006)
Language: English
ISBN: 0471666564

Data Mining with SQL Server 2005
Paperback: 480 pages
Publisher: Wiley (October 7, 2005)
Language: English
ISBN: 0471462616

Discovering Knowledge in Data: An Introduction to Data Mining
Hardcover: 240 pages
Publisher: Wiley-Interscience (November 18, 2004)
Language: English
ISBN: 0471666572

Exploratory Data Mining and Data Cleaning
Hardcover: 224 pages
Publisher: Wiley-Interscience; 1st edition (May 9, 2003)
Language: English
ISBN: 0471268518


The Handbook of Data Mining 
Paperback: 720 pages
Publisher: Lawrence Erlbaum Associates (November 30, 2004)
Language: English
ISBN: 0805855637

Business Modeling and Data Mining
Paperback: 650 pages
Publisher: Morgan Kaufmann; 1st edition (April 2003)
Language: English
ISBN: 155860653X


Data Mining: Concepts and Techniques
Hardcover: 500 pages
Publisher: Morgan Kaufmann; 1st edition (August 2000)
Language: English
ISBN: 1558604898

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition
Paperback: 560 pages
Publisher: Morgan Kaufmann; 2 edition (June 10, 2005)
Language: English
ISBN: 0120884070


Swarm Intelligence
Hardcover: 510 pages
Publisher: Morgan Kaufmann; 1st edition (March 23, 2001)
Language: English
ISBN: 1558605959

محب الله ورسوله · #3 (**permalink**) 30-11-2006, 01:44 PM

Marcus A. Maloof, «Machine Learning and Data Mining for Computer Security»
Publisher: Springer | Sep 2005 | ISBN: 184628029X | Pages: 210 | Format: PDF | Size: 2.8 MB

Intrusion detection and analysis has received a lot of criticism and publicity over the last several years. The Gartner report took a shot saying Intrusion Detection Systems are dead, while others believe Intrusion Detection is just reaching its maturity. The problem that few want to admit is that the current public methods of intrusion detection, while they might be mature, based solely on the fact they have been around for a while, are not extremely sophisticated and do not work very well. While there is no such thing as 100% security, people always expect a technology to accomplish more than it currently does, and this is clearly the case with intrusion detection. It needs to be taken to the next level with more advanced analysis being done by the computer and less by the human.

The current area of Intrusion Detection is begging for Machine Learning to be applied to it. Convergence of these two key areas is critical for it to be taken to the next level. The problem is that I have seen little research focusing on this, until now.

After reading Machine Learning and Data Mining for Computer Security, I feel Dr Maloof has hit the target dead centre. While much research has been done across Computer Security independently and Machine Learning independently, for some reason no one wanted to cross-breed the two topics.

Dr Maloof not only did a masterful job of focusing the book on a critical area that was in dire need of research, but he also strategically picked papers that complemented each other in a productive manner. Usually reading an edited volume like this, the chapters are very disjointed with no connection between them. While these chapters cover different areas of research, there is a hidden flow that complements the previous chapter with the next.

While Dr Maloof points out in his Preface the intended audience, I feel that there are two additional critical groups. Firstly, I feel that any vendor or solution provider that is looking to provide a competitive advantage for their product should read this book and see exactly what the potential of next generation intrusion detection can provide. Secondly, I feel that any Computer Science student should read this book to understand the power of convergence across technologies. Everyone is searching for new solutions to intrusion detection within Computer Science and more specifically within Computer Security. But until they are willing to take a step back and provide insight and knowledge from another domain, like Dr Maloof has done, they will not find suitable answers

______________________
http://depositfiles.com/files/409566
or
http://www.icefile.net/index.php?pag...r.Security.pdf
or
http://rapidshare.com/files/5375866/...r.Security.pdf

محب الله ورسوله · #4 (**permalink**) 26-10-2007, 12:55 PM

Data Quality: Concepts, Methodologies and Techniques (Data-Centric Systems and Applications)
By Carlo Batini,&nbspMonica Scannapieco,
* Publisher: Springer
* Number Of Pages: 262
* Publication Date: 2006-10-09
* ISBN / ASIN: 3540331727

Book Description:
Poor data quality can seriously hinder or damage the efficiency and effectiveness of organizations and businesses. The growing awareness of such repercussions has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament.

Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own quality problems.

This book is an ideal combination of the soundness of theoretical foundations and the applicability of practical approaches. It is ideally suited for everyone – researchers, students, or professionals – interested in a comprehensive overview of data quality issues. In addition, it will serve as the basis for an introductory course or for self-study on this topic

PDF, 3.49 MB
http://mihd.net/79t3ls
http://w13.easy-share.com/1181126.html
http://rapidshare.com/files/35218966...rg_datqual.rar

محب الله ورسوله · #5 (**permalink**) 05-11-2007, 08:41 PM

The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
By Ronen Feldman,&nbspJames Sanger,
* Publisher: Cambridge University Press
* Number Of Pages: 422
* Publication Date: 2006-12-11
* ISBN / ASIN: 0521836573
$70.00

Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities

Type: 423p PDF
Size: WinRAR-compressed to 4.19 MB
http://rapidshare.com/files/67476180...ldman36573.rar

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