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Abstract: Knowledge discovery in databases and data mining aim at semiautomatic tools for the analysis of large data sets. We consider some methods used in data mining, concentrating on levelwise search for all frequently occurring patterns. We show how this technique can be used in various applications. We also discuss possibilities for compiling data mining queries into algorithms, and look at the use of sampling in data mining. We conclude by listing several open research problems in data mining and... (Update)
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BibTeX entry: (Update)
Heikki Mannila. Methods and problem in data mining. In F. Afrati and P. Kolaitis, editors, Proceedings of International Conference on Database Theory, Greece, Jan 1997. Springer-Verlag. http://citeseer.ist.psu.edu/mannila97methods.html More
@inproceedings{ mannila97methods,
author = "Heikki Mannila",
title = "Methods and Problems in Data Mining",
booktitle = "{ICDT}",
pages = "41-55",
year = "1997",
url = "citeseer.ist.psu.edu/mannila97methods.html" }
Citations (may not include all citations):921 Mining association rules between sets of items in large data.. - Agrawal, Imielinski et al. - 1993
474 Advances in Knowledge Discovery and Data Mining (context) - Fayyad, Piatetsky-Shapiro et al. - 1996
400 Fast discovery of association rules (context) - Agrawal, Mannila et al. - 1996
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262 From data mining to knowledge discovery: An overview (context) - Fayyad, Piatetsky-Shapiro et al. - 1996
213 Discovery of multiple-level association rules from large dat.. - Han, Fu - 1995
209 Mining quantitative association rules in large relational - Srikant, Agrawal
204 tree: An index structure for high-dimensional data (context) - Berchtold, Keim et al. - 1996
189 Discovering frequent episodes in sequences (context) - Mannila, Toivonen et al. - 1995
186 Computational Geometry: An Introduction Through Randomized A.. (context) - Mulmuley - 1993
164 An efficient algorithm for mining association rules in large.. (context) - Savasere, Omiecinski et al. - 1995
137 Finding interesting rules from large sets of discovered asso.. - Klemettinen, Mannila et al. - 1994
89 A new SQL-like operator for mining association rules - Meo, Psaila et al. - 1996
85 Discovering generalized episodes using minimal occurrences - Mannila, Toivonen - 1996
74 Data mining using two-dimensional optimized association rule.. (context) - Fukuda - 1996
68 Controlling the complexity of learning in logic through synt.. - Kietz, Wrobel - 1992
67 Identifying the minimal transversals of a hypergraph and rel.. - Eiter, Gottlob - 1995
64 Design of Relational Databases (context) - Mannila, Raiha - 1992
60 A theory of clausal discovery (context) - De Raedt, Bruynooghe - 1993
57 Multiple uses of frequent sets and condensed representations - Mannila, Toivonen - 1996
51 First-order jk-clausal theories are PAC-learnable (context) - De Raedt, Dzeroski - 1994
46 A perspective on databases and data mining - Holsheimer, Kersten et al. - 1995
45 Design by example: An application of Armstrong relations (context) - Mannila, Raiha - 1986
41 Mining optimized association rules for numeric attributes (context) - Fukuda - 1996
41 Metaqueries for data mining - Shen, Ong et al. - 1996
36 Knowledge discovery from telecommunication network alarm dat.. - Hatonen, Klemettinen et al. - 1996
34 Automating the analysis and cataloging of sky surveys (context) - Fayyad, Djorgovski et al. - 1996
34 Developing tightly-coupled data mining applications on a rel.. - Agrawal, Shim - 1996
29 The power of sampling in knowledge discovery - Kivinen, Mannila - 1994
28 Automatic rule derivation for semantic query optimization (context) - Siegel - 1986
28 Data surveyor: Searching the nuggets in parallel (context) - Holsheimer, Kersten et al. - 1996
26 an algorithm for finding all interesting sentences (context) - Mannila, Toivonen - 1996
23 Discovering functional and inclusion dependencies in relatio.. (context) - Kantola, Mannila et al. - 1992
20 Visualization techniques for mining large databases: A compa.. - Keim, Kriegel - 1996
19 Approximate dependency inference from relations (context) - Kivinen, Mannila - 1995
17 Selecting and reporting what is interesting (context) - Matheus, Piatetsky-Shapiro et al. - 1996
14 Efficient discovery of interesting statements in databases (context) - Kloesgen - 1995
14 Data mining: machine learning (context) - Mannila - 1996
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3 the complexity of dependency inference (context) - Mannila, Raiha - 1992
3 Data mining as selective theory extraction in probabilistic .. - Jaeger, Mannila et al. - 1996
2 A database view on data mining (context) - Imielinski
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