| Description |
xiv, 611 pages : illustrations ; 23 cm |
| Contents |
From data mining to knowledge discovery : an overview / Usama M. Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth -- The process of knowlesge discovery in databases : a human-centered approach / Ronald J. Brachman and Tej Anand -- Graphical models for discovering knowledge / Wray Buntine -- A statistical perspective on knowledge discovery in databases / John Elder IV and Daryl Pregibon -- Inductive logic programming and knowledge discovery in databases / Sašo Džeroski -- Bayesian classification (AutoClass) : theory and results / Peter Cheeseman and John Stutz -- Discovering informative patterns and data cleaning / Isabelle Guyon, Nada Matič, and Valdimir Vapnik -- Transforming rules and trees into comprehensible knowledge structures / Brian R. Gaines -- Finding patterns in time series : a dynamic programming approach / Donald J. Berndt and James Clifford -- Explora : a multipattern and multistrategy discovery assistant / Willi Klösgen -- Bayesian networks for knowledge discovery / David Heckerman -- Fast discovery of association rules / Rakesh Agrawal ... [et al.] -- From contigency tables to various forms of knowledge in databases / Robert Zembowicz and Jan M. Żytkow -- Integrating inductive and deductive reasoning for data mining / Evangelos Simoudis, Brian Livezey, and Randy Kerber -- Metaqueries for data mining / Wei-Min Shen ... [et al.] -- Exploration of the power of attribute-oriented induction in data mining / Jiawei Han and Yongjian Fu -- Using inductive learning to generate rules for semantic query optimization / Chun-Nan Hsu and Craig A. Knoblock -- Data surveyor : searching the nuggets in parallel / Marcel Holsheimer, Martin L. Kersten, and Arno P.J.M. Siebes -- Automating the analysis and cataloging of sky surveys / Usama M. Fayyad, S. George Djorgovski, and Nicholas Weir -- Selecting and reporting what is interesting : the KEFIR application to healthcare data / Christopher J. Matheus, Gregory Piatetsky-Shapiro, and Dwight McNeill -- Modeling subjective uncertainty in image annotation / Padhraic Smyth ... [et al.] -- Predicting equity returns from securities data with minimal rule generation / Chidanand Apte and Se June Hong -- From data mining to knowledge discovery : current challenges and future directions / Ramasamy Uthurusamy -- Knowledge discovery in databases terminology / Willi Klösgen and Jan M. Żytkow -- Data mining and knowledge discovery Internet resources / Gregory Piatetsky-Shapiro |
| Summary |
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 |
| Analysis |
Databases |
|
Databases |
| Bibliography |
Includes bibliographical references and index |
| Issuing Body |
During the last decade, we have seen an explosive growth in our capabilities to both generate and collect data. Advances in data collection, widespread use of bar codes for most commercial products, and the computerization of many business and government transactions have flooded us with information, and generated an urgent need for new techniques and tools that can intelligently and automatically assist us in transforming this data into useful knowledge. This book examines and describes many such new techniques and tools, in the emerging field of data mining and knowledge discovery in databases (KDD). The chapters of this book, organized into eight sections, span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augmented database systems, and application case studies: Part One deals with fundamental issues in discovery; Part Two examines specific techniques for data mining. Part Three presents methods for dealing with trend and deviation analysis. Part Four focuses on data mining techniques for deriving dependencies. Part Five discusses integrated discovery systems. Part Six presents approaches for next-generation database systems Part Seven presents several real and successful applications. The Appendices provide a list of terms used in the literature of this fast-expanding field, and a list of online resources for the KDD researcher |
| Subject |
Artificial intelligence.
|
|
Data mining.
|
|
Databases.
|
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Knowledge acquisition (Expert systems)
|
|
Knowledge, Theory of.
|
| Author |
Fayyad, Usama M.
|
| LC no. |
95045329 |
| ISBN |
0262560976 |
|
