Advances in Knowledge Discovery and Data Mining

av Usama M Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, Ramasamy Uthurusamy. Häftad, 1996

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  • Häftad (Paperback)
  • Språk: Engelska
  • Antal sidor: 625
  • Utg.datum: 1996-03-01
  • Förlag: MIT Press
  • Illustrationer: index
  • Dimensioner: 230 x 155 x 35 mm
  • Vikt: 860 g
  • Antal komponenter: 1
  • ISBN: 9780262560979

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Övrig information

Gregory Piatetsky-Shapiro is Senior Member of Technical Staff and Principal Investigator of the Knowledge Discovery Project at GTE Laboratories.


From data mining to knowledge discovery: an overview, Usama M. Fayyad etal. Part 1 Foundations: The process of knowledge discovery in databases: a human-centred 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. Part 2 Classification and clustering: Inductive logic programming and knowledge discovery in databases, Saso Dzeroski; Bayesian classification (autoclass): theory and results, Peter Cheeseman and John Stutz; Discovering informative patterns and data cleaning, Isabelle Guyon et al; Transforming rules and trees into comprehensive structures, Brian R. Gaines. Part 3 Trend and deviation analysis: Finding patterns in time series: a dynamic programming approach, Donald J. Berndt and James Clifford; explore: a multipattern and multistrategy discovery assistant, Willi Klosgen. Part 4 Dependency derivation: Bayesian networks for knowledge discovery, David Heckerman; Fast discovery of association rules, Rakesh Agrawal et al; From contingency tables to variation forms of knowledge in databases, Robert Zembowicz and Jan M. Zytkow. Part 5 Integrated discovery systems: Integrating inductive and deductive reasoning for data mining, Evangelos Simoudis, et al; 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. Part 6 Next generation database systems: 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, et al. Part 7 Automating the analysis and cataloguing of sky surveys, Usama M. Fayyad et al; Selecting and reporting what is interesting: the KEFIR application to healthcare data, Christopher J. Matheus; 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. Appendices: Knowledge discovery in databases terminology; data mining, and knowledge discovery Internet resources, Gregory Piatetsky-Shapiro.