Commercial Data Mining

• Author : David Nettleton
• Publisher : Elsevier
• Release : 29 January 2014

Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business

• Author : Anoop Singhal
• Publisher : Springer Science & Business Media
• Release : 06 April 2007

The application of data warehousing and data mining techniques to computer security is an important emerging area, as information processing and internet accessibility costs decline and more and more organizations become vulnerable to cyber attacks. These security breaches include attacks on single computers, computer networks, wireless networks, databases, or authentication compromises. This book describes data warehousing and data mining techniques that can be used to detect attacks. It is designed to be a useful handbook for practitioners and researchers in

• Author : S. Sumathi,S.N. Sivanandam
• Publisher : Springer Science & Business Media
• Release : 26 September 2006

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for

• Author : Stéphane Tufféry
• Publisher : John Wiley & Sons
• Release : 23 March 2011

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such

• Author : Linda D. Koontz
• Publisher : DIANE Publishing
• Release : 01 November 2005

Data mining -- a technique for extracting knowledge from large volumes of data -- is being used increasingly by the gov't. & by the private sector. Many fed. data mining efforts involve the use of personal information, which can originate from gov't. sources as well as private sector organizations. The federal government's increased use of data mining since the terrorist attacks of Sept. 11, 2001, has raised public & congressional concerns. This report describes the characteristics of 5 federal data mining efforts & determines whether agencies

• Author : Anonim
• Publisher : DIANE Publishing
• Release : 27 January 2023

• Author : Gordon S. Linoff,Michael J. A. Berry
• Publisher : John Wiley & Sons
• Release : 23 March 2011

The leading introductory book on data mining, fully updated andrevised! When Berry and Linoff wrote the first edition of Data MiningTechniques in the late 1990s, data mining was just starting tomove out of the lab and into the office and has since grown tobecome an indispensable tool of modern business. This newedition—more than 50% new and revised— is asignificant update from the previous one, and shows you how toharness the newest data mining methods and techniques to solvecommon business problems.

• Author : Hamparsum Bozdogan
• Publisher : CRC Press
• Release : 29 July 2003

Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering. Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to

• Author : Thomas Reinartz
• Publisher : Springer
• Release : 31 July 2003

In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application

• Author : David Nettleton
• Publisher : Morgan Kaufmann
• Release : 27 January 2023

Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business

• Author : Mehmed Kantardzic
• Publisher : John Wiley & Sons
• Release : 23 October 2019

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on

• Author : John Wang
• Publisher : IGI Global
• Release : 01 January 2003

Data Mining: Opportunities and Challenges presents an overview of the state of the art approaches in this new and multidisciplinary field of data mining. The primary objective of this book is to explore the myriad issues regarding data mining, specifically focusing on those areas that explore new methodologies or examine case studies. This book contains numerous chapters written by an international team of forty-four experts representing leading scientists and talented young scholars from seven different countries.

• Author : Management Association, Information Resources
• Publisher : IGI Global
• Release : 30 November 2012

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.

• Author : Anonim
• Publisher : DEStech Publications, Inc
• Release : 07 January 2014

SPBEI 2013 aims to be an excellent platform to facilitate international exchange of state-ofthe- art research and practice in image, video, and signal processing, biomedical engineering, informatics, and their cross-intersection to catalyze innovative research ideas and to dissimilate new scientific discoveries. The nature of the research demands collaboration in medicine, biology, physics, engineering, computer science, and statistics; and SPBEI attempts to expedite and strengthen the exploration and systemization of interdisciplinary knowledge. This year, the conference received a large number of submissions

• Author : Thomas Hoeren,Barbara Kolany-Raiser
• Publisher : Springer
• Release : 17 October 2017

This book is open access under a CC BY 4.0 license. This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive