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Advances in Knowledge Discovery and Data Mining

1996 Computers
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Release : 1996
Genre : Computers
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Advances in Knowledge Discovery and Data Mining by : Usama M. Fayyad

Download or read book Advances in Knowledge Discovery and Data Mining written by Usama M. Fayyad. This book was released on 1996. Available in PDF, EPUB and Kindle. Book excerpt: Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.

Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends

2011-12-31 Computers
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Release : 2011-12-31
Genre : Computers
Kind : eBook
Book Rating : 756/5 ( reviews)

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Book Synopsis Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends by : Taniar, David

Download or read book Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends written by Taniar, David. This book was released on 2011-12-31. Available in PDF, EPUB and Kindle. Book excerpt: "This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.

Advances in Machine Learning and Data Mining for Astronomy

2012-03-29 Computers
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Release : 2012-03-29
Genre : Computers
Kind : eBook
Book Rating : 748/5 ( reviews)

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Book Synopsis Advances in Machine Learning and Data Mining for Astronomy by : Michael J. Way

Download or read book Advances in Machine Learning and Data Mining for Astronomy written by Michael J. Way. This book was released on 2012-03-29. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines

Recent Advances in Data Mining of Enterprise Data

2008-01-15 Business & Economics
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Release : 2008-01-15
Genre : Business & Economics
Kind : eBook
Book Rating : 868/5 ( reviews)

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Book Synopsis Recent Advances in Data Mining of Enterprise Data by : T. Warren Liao

Download or read book Recent Advances in Data Mining of Enterprise Data written by T. Warren Liao. This book was released on 2008-01-15. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."

Applications of Data Mining in Computer Security

2002-05-31 Business & Economics
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Release : 2002-05-31
Genre : Business & Economics
Kind : eBook
Book Rating : 549/5 ( reviews)

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Book Synopsis Applications of Data Mining in Computer Security by : Daniel Barbará

Download or read book Applications of Data Mining in Computer Security written by Daniel Barbará. This book was released on 2002-05-31. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security. Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.

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