Efficiently Mining Long Patterns from Databases.

Roberto J. Bayardo Jr.: Efficiently Mining Long Patterns from Databases. SIGMOD Conference 1998: 85-93

@inproceedings{DBLP:conf/sigmod/Bayardo98,
  author    = {Roberto J. Bayardo Jr.},
  editor    = {Laura M. Haas and
               Ashutosh Tiwary},
  title     = {Efficiently Mining Long Patterns from Databases},
  booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
               on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
  publisher = {ACM Press},
  year      = {1998},
  isbn      = {0-89791-995-5},
  pages     = {85-93},
  ee        = {http://doi.acm.org/10.1145/276304.276313, db/conf/sigmod/Bayardo98.html},
  crossref  = {DBLP:conf/sigmod/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

We present a pattern-mining algorithm that scales roughly linearly in the number of maximal patterns embedded in a database irrespective of the length of the longest pattern. In comparison, previous algorithms based on Apriori scale exponentially with longest pattern length. Experiments on real data show that when the patterns are long, our algorithm is more efficient by an order of magnitude or more.

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BibTeX

Printed Edition

Laura M. Haas, Ashutosh Tiwary (Eds.): SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA. ACM Press 1998, ISBN 0-89791-995-5 BibTeX , SIGMOD Record 27(2), June 1998
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References

[1]: Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference 1993: 207-216 BibTeX
[2]: ...
[3]: ...
[4]: Rakesh Agrawal, Ramakrishnan Srikant: Mining Sequential Patterns. ICDE 1995: 3-14 BibTeX
[5]: ...
[6]: Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, Shalom Tsur: Dynamic Itemset Counting and Implication Rules for Market Basket Data. SIGMOD Conference 1997: 255-264 BibTeX
[7]: Dimitrios Gunopulos, Heikki Mannila, Sanjeev Saluja: Discovering All Most Specific Sentences by Randomized Algorithms. ICDT 1997: 215-229 BibTeX
[8]: Dao-I Lin, Zvi M. Kedem: Pincer Search: A New Algorithm for Discovering the Maximum Frequent Set. EDBT 1998: 105-119 BibTeX
[9]: Jong Soo Park, Ming-Syan Chen, Philip S. Yu: An Effective Hash Based Algorithm for Mining Association Rules. SIGMOD Conference 1995: 175-186 BibTeX
[10]: Ron Rymon: Search through Systematic Set Enumeration. KR 1992: 539-550 BibTeX
[11]: Ashok Savasere, Edward Omiecinski, Shamkant B. Navathe: An Efficient Algorithm for Mining Association Rules in Large Databases. VLDB 1995: 432-444 BibTeX
[12]: ...
[13]: Padhraic Smyth, Rodney M. Goodman: An Information Theoretic Approach to Rule Induction from Databases. IEEE Trans. Knowl. Data Eng. 4(4): 301-316(1992) BibTeX
[14]: Ramakrishnan Srikant, Rakesh Agrawal: Mining Sequential Patterns: Generalizations and Performance Improvements. EDBT 1996: 3-17 BibTeX
[15]: ...
[16]: ...

Referenced by

Jiawei Han, Jian Pei, Yiwen Yin: Mining Frequent Patterns without Candidate Generation. SIGMOD Conference 2000: 1-12
Shinichi Morishita, Jun Sese: Traversing Itemset Lattice with Statistical Metric Pruning. PODS 2000: 226-236
Laks V. S. Lakshmanan, Raymond T. Ng, Jiawei Han, Alex Pang: Optimization of Constrained Frequent Set Queries with 2-variable Constraints. SIGMOD Conference 1999: 157-168
Christian Hidber: Online Association Rule Mining. SIGMOD Conference 1999: 145-156
Nicolas Pasquier, Yves Bastide, Rafik Taouil, Lotfi Lakhal: Discovering Frequent Closed Itemsets for Association Rules. ICDT 1999: 398-416
Jiawei Han, Guozhu Dong, Yiwen Yin: Efficient Mining of Partial Periodic Patterns in Time Series Database. ICDE 1999: 106-115
Brian Dunkel, Nandit Soparkar: Data Organization and Access for Efficient Data Mining. ICDE 1999: 522-529
Roberto J. Bayardo Jr., Rakesh Agrawal, Dimitrios Gunopulos: Constraint-Based Rule Mining in Large, Dense Databases. ICDE 1999: 188-197
Philip S. Yu: Data Mining and Personalization Technologies. DASFAA 1999: 6-13
Suh-Ying Wur, Yungho Leu: An Effective Boolean Algorithm for Mining Association Rules in Large Databases. DASFAA 1999: 179-186
Charu C. Aggarwal, Philip S. Yu: Mining Large Itemsets for Association Rules. IEEE Data Eng. Bull. 21(1): 23-31(1998)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan: Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. SIGMOD Conference 1998: 94-105

BibTeX

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