Commercial Data Mining

Commercial Data Mining
Author: David Nettleton
Publsiher: Elsevier
Total Pages: 304
Release: 2014-01-29
ISBN 10: 012416658X
ISBN 13: 9780124166585
Language: EN, FR, DE, ES & NL

Commercial Data Mining Book Review:

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 objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. Illustrates cost-benefit evaluation of potential projects Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools Approachable reference can be read from cover to cover by readers of all experience levels Includes practical examples and case studies as well as actionable business insights from author's own experience

Data Mining Southeast Asia Edition

Data Mining  Southeast Asia Edition
Author: Jiawei Han,Jian Pei,Micheline Kamber
Publsiher: Elsevier
Total Pages: 800
Release: 2006-04-06
ISBN 10: 9780080475585
ISBN 13: 0080475582
Language: EN, FR, DE, ES & NL

Data Mining Southeast Asia Edition Book Review:

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects Complete classroom support for instructors at www.mkp.com/datamining2e companion site

Data Warehousing and Data Mining Techniques for Cyber Security

Data Warehousing and Data Mining Techniques for Cyber Security
Author: Anoop Singhal
Publsiher: Springer Science & Business Media
Total Pages: 159
Release: 2007-04-06
ISBN 10: 0387476539
ISBN 13: 9780387476537
Language: EN, FR, DE, ES & NL

Data Warehousing and Data Mining Techniques for Cyber Security Book Review:

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 industry, and is also suitable as a text for advanced-level students in computer science.

Introduction to Data Mining and Its Applications

Introduction to Data Mining and Its Applications
Author: S. Sumathi,S.N. Sivanandam
Publsiher: Springer Science & Business Media
Total Pages: 828
Release: 2006-09-26
ISBN 10: 3540343504
ISBN 13: 9783540343509
Language: EN, FR, DE, ES & NL

Introduction to Data Mining and Its Applications Book Review:

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 a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.

Principles of Data Mining

Principles of Data Mining
Author: Max Bramer
Publsiher: Springer
Total Pages: 526
Release: 2016-11-09
ISBN 10: 1447173074
ISBN 13: 9781447173076
Language: EN, FR, DE, ES & NL

Principles of Data Mining Book Review:

This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

Data Mining and Statistics for Decision Making

Data Mining and Statistics for Decision Making
Author: Stéphane Tufféry
Publsiher: John Wiley & Sons
Total Pages: 716
Release: 2011-03-23
ISBN 10: 9780470979280
ISBN 13: 0470979283
Language: EN, FR, DE, ES & NL

Data Mining and Statistics for Decision Making Book Review:

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 as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Data Mining Techniques

Data Mining Techniques
Author: Michael J. A. Berry,Gordon S. Linoff
Publsiher: John Wiley & Sons
Total Pages: 643
Release: 2004-04-09
ISBN 10: 0471470643
ISBN 13: 9780471470649
Language: EN, FR, DE, ES & NL

Data Mining Techniques Book Review:

Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Data Mining

Data Mining
Author: Linda D. Koontz
Publsiher: DIANE Publishing
Total Pages: 76
Release: 2005-11
ISBN 10: 9781422302668
ISBN 13: 1422302660
Language: EN, FR, DE, ES & NL

Data Mining Book Review:

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 are providing adequate privacy & security protection for the information systems used in the efforts & for individuals potentially affected by these data mining efforts. Includes recommendations. Charts & tables.

Balancing Privacy Security The Privacy Implications of Government Data Mining Programs Congressional Hearing

Balancing Privacy   Security  The Privacy Implications of Government Data Mining Programs  Congressional Hearing
Author: Anonim
Publsiher: DIANE Publishing
Total Pages: 135
Release: 2022
ISBN 10: 9781422320259
ISBN 13: 1422320251
Language: EN, FR, DE, ES & NL

Balancing Privacy Security The Privacy Implications of Government Data Mining Programs Congressional Hearing Book Review:

Data Mining Techniques

Data Mining Techniques
Author: Gordon S. Linoff,Michael J. A. Berry
Publsiher: John Wiley & Sons
Total Pages: 888
Release: 2011-03-23
ISBN 10: 9781118087459
ISBN 13: 1118087453
Language: EN, FR, DE, ES & NL

Data Mining Techniques Book Review:

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. The duo of unparalleled authors shareinvaluable advice for improving response rates to direct marketingcampaigns, identifying new customer segments, and estimating creditrisk. In addition, they cover more advanced topics such aspreparing data for analysis and creating the necessaryinfrastructure for data mining at your company. Features significant updates since the previous edition andupdates you on best practices for using data mining methods andtechniques for solving common business problems Covers a new data mining technique in every chapter along withclear, concise explanations on how to apply each techniqueimmediately Touches on core data mining techniques, including decisiontrees, neural networks, collaborative filtering, association rules,link analysis, survival analysis, and more Provides best practices for performing data mining using simpletools such as Excel Data Mining Techniques, Third Edition covers a new datamining technique with each successive chapter and then demonstrateshow you can apply that technique for improved marketing, sales, andcustomer support to get immediate results.

Data Mining Models

Data Mining Models
Author: David L. Olson
Publsiher: Business Expert Press
Total Pages: 173
Release: 2016-06-27
ISBN 10: 163157549X
ISBN 13: 9781631575495
Language: EN, FR, DE, ES & NL

Data Mining Models Book Review:

Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the data mining process, to include problem identification, data management, and available modeling tools. The book takes the approach of demonstrating typical business data sets with open source software. KNIME is a very easy-to-use tool, and is used as the primary means of demonstration. R is much more powerful and is a commercially viable data mining tool. We also demonstrate WEKA, which is a highly useful academic software, although it is difficult to manipulate test sets and new cases, making it problematic for commercial use.

Visual Data Mining

Visual Data Mining
Author: Tom Soukup,Ian Davidson
Publsiher: John Wiley & Sons
Total Pages: 416
Release: 2002-09-18
ISBN 10: 0471271381
ISBN 13: 9780471271383
Language: EN, FR, DE, ES & NL

Visual Data Mining Book Review:

Marketing analysts use data mining techniques to gain a reliable understanding of customer buying habits and then use that information to develop new marketing campaigns and products. Visual mining tools introduce a world of possibilities to a much broader and non-technical audience to help them solve common business problems. Explains how to select the appropriate data sets for analysis, transform the data sets into usable formats, and verify that the sets are error-free Reviews how to choose the right model for the specific type of analysis project, how to analyze the model, and present the results for decision making Shows how to solve numerous business problems by applying various tools and techniques Companion Web site offers links to data visualization and visual data mining tools, and real-world success stories using visual data mining

Statistical Data Mining and Knowledge Discovery

Statistical Data Mining and Knowledge Discovery
Author: Hamparsum Bozdogan
Publsiher: CRC Press
Total Pages: 624
Release: 2003-07-29
ISBN 10: 1135441022
ISBN 13: 9781135441029
Language: EN, FR, DE, ES & NL

Statistical Data Mining and Knowledge Discovery Book Review:

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 discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward K. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications.

Focusing Solutions for Data Mining

Focusing Solutions for Data Mining
Author: Thomas Reinartz
Publsiher: Springer
Total Pages: 316
Release: 2003-07-31
ISBN 10: 3540483160
ISBN 13: 9783540483168
Language: EN, FR, DE, ES & NL

Focusing Solutions for Data Mining Book Review:

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 domains. The book provides various appendicies enhancing easy accessibility. The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

Ethical Data Mining Applications for Socio Economic Development

Ethical Data Mining Applications for Socio Economic Development
Author: Hakikur Rahman,Isabel Ramos
Publsiher: IGI Global
Total Pages: 349
Release: 2013-05-31
ISBN 10: 1466640790
ISBN 13: 9781466640795
Language: EN, FR, DE, ES & NL

Ethical Data Mining Applications for Socio Economic Development Book Review:

"This book provides an overview of data mining techniques under an ethical lens, investigating developments in research best practices and examining experimental cases to identify potential ethical dilemmas in the information and communications technology sector"--Provided by publisher.

Data Mining and Knowledge Discovery Handbook

Data Mining and Knowledge Discovery Handbook
Author: Oded Maimon,Oded Z. Maimon,Lior Rokach
Publsiher: Springer Science & Business Media
Total Pages: 1383
Release: 2005
ISBN 10: 9780387244358
ISBN 13: 0387244352
Language: EN, FR, DE, ES & NL

Data Mining and Knowledge Discovery Handbook Book Review:

Organizes major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD). This book provides algorithmic descriptions of classic methods, and also suitable for professionals in fields such as computing applications, information systems management, and more.

MASTERING DATA MINING THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT

MASTERING DATA MINING  THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT
Author: Michael J. A. Berry,Gordon S. Linoff
Publsiher: Unknown
Total Pages: 512
Release: 2008-09-01
ISBN 10: 9788126518258
ISBN 13: 8126518251
Language: EN, FR, DE, ES & NL

MASTERING DATA MINING THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT Book Review:

Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers.

Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications
Author: R.L. Grossman,C. Kamath,P. Kegelmeyer,V. Kumar,R. Namburu
Publsiher: Springer Science & Business Media
Total Pages: 605
Release: 2013-12-01
ISBN 10: 1461517338
ISBN 13: 9781461517337
Language: EN, FR, DE, ES & NL

Data Mining for Scientific and Engineering Applications Book Review:

Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Data Mining

Data Mining
Author: John Wang
Publsiher: IGI Global
Total Pages: 484
Release: 2003-01-01
ISBN 10: 1591400953
ISBN 13: 9781591400950
Language: EN, FR, DE, ES & NL

Data Mining Book Review:

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.

Data Mining

Data Mining
Author: Bhavani Thuraisingham
Publsiher: CRC Press
Total Pages: 288
Release: 2014-01-23
ISBN 10: 1482252503
ISBN 13: 9781482252507
Language: EN, FR, DE, ES & NL

Data Mining Book Review:

Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues. This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence. Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.