ACM SIGMOD Anthology ACM SIGMOD dblp.uni-trier.de

Methods and Problems in Data Mining.

Heikki Mannila: Methods and Problems in Data Mining. ICDT 1997: 41-55
@inproceedings{DBLP:conf/icdt/Mannila97,
  author    = {Heikki Mannila},
  editor    = {Foto N. Afrati and
               Phokion G. Kolaitis},
  title     = {Methods and Problems in Data Mining},
  booktitle = {Database Theory - ICDT '97, 6th International Conference, Delphi,
               Greece, January 8-10, 1997, Proceedings},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {1186},
  year      = {1997},
  isbn      = {3-540-62222-5},
  pages     = {41-55},
  ee        = {db/conf/icdt/Mannila97.html},
  crossref  = {DBLP:conf/icdt/97},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

ACM SIGMOD Anthology

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References

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Rakesh Agrawal, Heikki Mannila, Ramakrishnan Srikant, Hannu Toivonen, A. Inkeri Verkamo: Fast Discovery of Association Rules. Advances in Knowledge Discovery and Data Mining 1996: 307-328 BibTeX
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Contents BibTeX
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Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama: Data Mining Using Two-Dimensional Optimized Accociation Rules: Scheme, Algorithms, and Visualization. SIGMOD Conference 1996: 13-23 BibTeX
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Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama: Mining Optimized Association Rules for Numeric Attributes. PODS 1996: 182-191 BibTeX
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Contents BibTeX
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Jim Gray, Adam Bosworth, Andrew Layman, Hamid Pirahesh: Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total. ICDE 1996: 152-159 BibTeX
[16]
Jiawei Han, Yongjian Fu: Discovery of Multiple-Level Association Rules from Large Databases. VLDB 1995: 420-431 BibTeX
[17]
Kimmo Hätönen, Mika Klemettinen, Heikki Mannila, Pirjo Ronkainen, Hannu Toivonen: Knowledge Discovery from Telecommunication Network Alarm Databases. ICDE 1996: 115-122 BibTeX
[18]
Marcel Holsheimer, Martin L. Kersten, Heikki Mannila, Hannu Toivonen: A Perspective on Databases and Data Mining. KDD 1995: 150-155 BibTeX
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[21]
Tomasz Imielinski, Heikki Mannila: A Database Perspective on Knowledge Discovery. Commun. ACM 39(11): 58-64(1996) BibTeX
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Daniel A. Keim, Hans-Peter Kriegel: Visualization Techniques for Mining Large Databases: A Comparison. IEEE Trans. Knowl. Data Eng. 8(6): 923-938(1996) BibTeX
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Jyrki Kivinen, Heikki Mannila: The Power of Sampling in Knowledge Discovery. PODS 1994: 77-85 BibTeX
[28]
Jyrki Kivinen, Heikki Mannila: Approximate Inference of Functional Dependencies from Relations. Theor. Comput. Sci. 149(1): 129-149(1995) BibTeX
[29]
Mika Klemettinen, Heikki Mannila, Pirjo Ronkainen, Hannu Toivonen, A. Inkeri Verkamo: Finding Interesting Rules from Large Sets of Discovered Association Rules. CIKM 1994: 401-407 BibTeX
[30]
Willi Klösgen: Efficient Discovery of Interesting Statements in Databases. J. Intell. Inf. Syst. 4(1): 53-69(1995) BibTeX
[31]
Heikki Mannila: Data Mining: Machine Learning, Statistics, and Databases. SSDBM 1996: 2-9 BibTeX
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Heikki Mannila, Kari-Jouko Räihä: Design by Example: An Application of Armstrong Relations. J. Comput. Syst. Sci. 33(2): 126-141(1986) BibTeX
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[35]
Heikki Mannila, Hannu Toivonen: Discovering Generalized Episodes Using Minimal Occurrences. KDD 1996: 146-151 BibTeX
[36]
Heikki Mannila, Hannu Toivonen: Multiple Uses of Frequent Sets and Condensed Representations (Extended Abstract). KDD 1996: 189-194 BibTeX
[37]
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[38]
Heikki Mannila, Hannu Toivonen, A. Inkeri Verkamo: Discovering Frequent Episodes in Sequences. KDD 1995: 210-215 BibTeX
[39]
Christopher J. Matheus, Gregory Piatetsky-Shapiro, Dwight McNeill: Selecting and reporting What Is Interesting. Advances in Knowledge Discovery and Data Mining 1996: 495-515 BibTeX
[40]
Rosa Meo, Giuseppe Psaila, Stefano Ceri: A New SQL-like Operator for Mining Association Rules. VLDB 1996: 122-133 BibTeX
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Balaji Padmanabhan, Alexander Tuzhilin: Pattern Discovery in Temporal Databases: A Temporal Logic Approach. KDD 1996: 351-354 BibTeX
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Ashok Savasere, Edward Omiecinski, Shamkant B. Navathe: An Efficient Algorithm for Mining Association Rules in Large Databases. VLDB 1995: 432-444 BibTeX
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Wei-Min Shen, KayLiang Ong, Bharat G. Mitbander, Carlo Zaniolo: Metaqueries for Data Mining. Advances in Knowledge Discovery and Data Mining 1996: 375-398 BibTeX
[46]
Michael Siegel: Automatic Rule Derivation For Semantic Query Optimization. Expert Database Conf. 1988: 669-698 BibTeX
[47]
Ramakrishnan Srikant, Rakesh Agrawal: Mining Quantitative Association Rules in Large Relational Tables. SIGMOD Conference 1996: 1-12 BibTeX
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Hannu Toivonen: Sampling Large Databases for Association Rules. VLDB 1996: 134-145 BibTeX
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Referenced by

  1. Luc Boasson, Patrick Cégielski, Irène Guessarian, Yuri Matiyasevich: Window-Accumulated Subsequence Matching Problem is Linear. PODS 1999: 327-336
  2. Shalom Tsur, Jeffrey D. Ullman, Serge Abiteboul, Chris Clifton, Rajeev Motwani, Svetlozar Nestorov, Arnon Rosenthal: Query Flocks: A Generalization of Association-Rule Mining. SIGMOD Conference 1998: 1-12
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