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From Data Mining to Knowledge Discovery in Databases (1996) [164 citations — 0 self]

by Usama Fayyad ,  Gregory Piatetsky-shapiro ,  Padhraic Smyth
AI Magazine
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Abstract:

This article provides an overview of this emerging field, clarifying how data mining and knowledge

Citations

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3356 C4.5: Programs for Machine Learning – Quinlan - 1993
2573 Classification and Regression Trees – Breiman, Friedman, et al. - 1984
1478 Algorithms for Clustering Data – Jain, Dubes - 1988
1058 Density Estimation for Statistics and Data Analysis – Silverman - 1986
989 Case-based Reasoning – Kolodner - 1993
470 From data mining to knowledge discovery: An overview – Fayyad, Piatetsky-Shapiro, et al. - 1996
361 Bayesian classification (AutoClass): Theory and results – Cheeseman, Stutz - 1995
342 Fast discovery of association rules – Agrawal, Mannil, et al. - 1996
271 Causation, Prediction and Search – Spirtes, Glymour, et al. - 2000
266 Graphical Models in Applied Multivariate Statistics – Whittaker - 1990
202 The merge/purge problem for large databases – Hernandez, Stolfo - 1995
199 Nearest Neighbor (NN) Norms: NN Pattern Recognition Classification Techniques – Dasarathy - 1991
196 Discovering frequent episodes in sequences – Mannila, Toivonen, et al. - 1995
193 Computer Systems That Learn: Classification and Prediction Methods from Statistics – Weiss, Kulikowski - 1991
180 Detection of Abrupt Changes: Theory and Application – Basseville, Nikiforov - 1993
137 Providing OLAP (on-line analytical processing) to user-analysts: An IT mandate – Codd - 1993
121 The process of knowledge discovery in databases: A human-centered approach – Brachman, Anand - 1996
105 Unexpectedness as a measure of interestingness in knowledge discovery – PADMANABHAN, TUZHILIN - 1999
104 Neural networks and related methods for classification (with discussion – Ripley - 1994
99 Discrimination and Classification – Hand - 1981
95 Finding patterns in time series: a dynamic programming approach – Berndt - 1996
82 The interestingness of deviations – PIATETSKY-SHAPIRO, MATHEUS - 1994
78 Multivatiate adaptive regression splines. The Annals of Statistics – Friedman - 1991
54 Discovering Causal Structure – Glymour, Scheines, et al. - 1987
52 Bayesian networks for knowledge discovery – Heckerman - 1996
49 Inductive logic programming and knowledge discovery in databases – Dzeroski - 1996
48 The world wide web: Quagmire or gold mine – Etzioni - 1996
40 Discovering informative patterns and data cleaning – Guyon, Matic - 1996
36 On finding the most probable model – Cheeseman - 1990
36 Selecting among rules induced from a hurricane database – Major, Mangano - 1993
33 KDD for science data analysis: Issues and examples – Fayyad, Haussler, et al. - 1996
26 Data surveyor: Searching the nuggets in parallel – Holsheimer, Kersten, et al. - 1996
25 Predicting equity returns from securities data with minimal rule generation – Apte, Hong - 1996
24 Relationship marketing – Berry - 1983
23 Active data mining – Agrawal, Psaila - 1995
23 Graphical Models for Discovering Knowledge – Buntine - 1996
23 Fast spatiotemporal data mining of large geophysical datasets – Stolorz - 1995
16 Deconstructing Statistical Questions – Hand - 1994
16 Selecting and reporting what is interesting: The KEFIR application to healthcare data – Matheus, Piatetsky-Shapiro, et al. - 1996
15 Analyzing the benefits of domain knowledge in substructure discovery – Djoko, Cook - 1995
14 An overview of issues in developing industrial data mining and knowledge discovery applications – Piatetsky-Shapiro, Brachman, et al. - 1996
12 R.: "Using Recon for Data Cleaning – Simoudis, Livezey, et al. - 1995
11 EXPLORA: A multipattern and multistrategy discovery assistant – Kloesgen - 1996
11 Knowledge discovery in database terminology – Klosgen, Zytkow - 1996
9 From digitized images to online catalogs --- data mining a sky survey – FAYYAD, DJORGOVSKI - 1996
9 Knowledge Discovery in real databases: A report on the IJCAI-89 Workshop – Piatetsky-Shapiro - 1991
8 A statistical perspective on kdd – Elder, Pregibon - 1996
8 The financial crimes enforcement network AI system (FAIS): Identifying potential money laundering from reports of large cash transactions – Senator, Goldberg, et al. - 1995
4 Applying Classification Algorithms – Brodley, Smyth - 1996
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