[CENTER]Applied Data Mining
Statistical Methods for Business and Industry

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Title : Applied Data Mining
Author : Paolo Giudici
Publisher : John Wiley & Sons
iSBN : 047084678X
Format : PDF
Size : 5.6MB
Amazon : h**p://www.amazon.com/gp/product/047084678X/



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The increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. Applied Data Mining: Statistical Methods for Business and Industry provides an accessible introduction to data mining methods in a consistent and application-oriented statistical framework. It describes six case studies, taken from real industry projects, highlighting the current applications of data mining methods. Provides an introduction to data mining methods and applications. Includes coverage of classical and Bayesian multivariate statistical methodology as well as of machine learning and computational data mining methods. Includes many recent developments, such as association and sequence rules, graphical Markov models, memory-based reasoning, credit risk and web mining. Features a number of detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, and the case studies are analysed using SAS and SAS Enterprise Miner. Accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining: Statistical Methods for Business and Industry is primarily aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies give guidance to professionals working in industry on projects involving large volumes of data, such as in customer relationship management, web design, risk management, marketing, economics and finance.


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[CENTER]Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)

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Title : Data Mining with Computational Intelligence
Author : Lipo Wang
Publisher : Springer
iSBN : 3540245227
Format : PDF
Size : 4.6MB
Amazon : h**p://www.amazon.com/gp/product/3540245227/



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Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.

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[CENTER]Data Mining: Practical Machine Learning Tools and Techniques

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Title : Data Mining: Practical Machine Learning Tools and Techniques
Author : Ian H. Witten
Publisher : Morgan Kaufmann
iSBN : 0120884070
Format : PDF
Size : 7.9MB
Amazon : h**p://www.amazon.com/gp/product/0120884070/



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As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work.

The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more.




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[CENTER]Business Modeling and Data Mining

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Title : Business Modeling and Data Mining
Author : Dorian Pyle
Publisher :Morgan Kaufmann
iSBN : 155860653X
Format : CHM
Size : 11.1MB
Amazon : h**p://www.amazon.com/exec/obidos/tg/detail/-/155860653X/



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Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem.

This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.

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[CENTER]Managing Data Mining Technologies in Organizations:
Techniques and Applications

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Title ..............: Managing Data Mining Technologies in Organizations
Author ..........: Parag Pendharkar
Publisher ......: Idea Group Publishing
iSBN .............: 1591400570
Format ...........: CHM
Size ...............: 4.86MB
Amazon .........: h**p://www.amazon.com/exec/obidos/tg/detail/-/1591400570/



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This book constitutes the refereed proceedings of the 9th International Conference on Database Systems for Advanced Applications, DASFAA 2004, held in Jeju Island, Korea in March 2004. The 60 revised full papers and 18 revised short papers presented together with 2 invited articles were carefully reviewed and seleted from 272 submissions. The papers are organized in topical sections on access methods, query processing in XML, security and integrity, query processing in temporal and spatial databases, semi-structured databases, knowledge discovery in temporal and spatial databases, XML and multimedia and knowledge discovery on the Web, query processing and optimization, classification and clustering, Web search, mobile databases, parallel and distributed databases, and multimedia databases.



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[CENTER]Intelligent Agents for Data Mining and Information Retrieval

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Title ....................: Intelligent Agents for Data Mining and Information Retrieval
Author ................: Masoud Mohammadian
Publisher ............: Idea Group Publishing
iSBN ..................: 1591401941
Format ................: CHM
Size ....................: 8.13MB
Amazon ..............: h**p://www.amazon.com/exec/obidos/tg/detail/-/1591401941/



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There is a large increase in the amount of information available on World Wide Web and also in number of online databases. This information abundance increases the complexity of locating relevant information. Such a complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent Agents are currently used to improve the search and retrieval information on World Wide Web. The use of existing search and retrieval engines with the addition of intelligent agents allows a more comprehensive search with a performance that can be measured. Intelligent Agents for Mining and Information Retrieval discusses the foundation as well as the pratical side of intelligent agents and their theory and applications for web data mining and information retrieval. The book can used for researchers at the undergraduate and post-graduate levels as well as a reference of the state-of-art for cutting edge researchers.



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