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Online algorithms for finding profile association rules
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Source Conference on Information and Knowledge Management archive
Proceedings of the seventh international conference on Information and knowledge management table of contents
Bethesda, Maryland, United States
Pages: 86 - 95  
Year of Publication: 1998
ISBN:1-58113-061-9
Authors
Charų C. Aggarwal  T.J. Watson Research Center, Yorktown Heights, NY
Zheng Sun  Duke University, Durham, NC
Philip S. Yu  T.J. Watson Research Center, Yorktown Heights, NY
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
SIGMIS: ACM Special Interest Group on Management Information Systems
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 20,   Citation Count: 4
Additional Information:

references   cited by   index terms   collaborative colleagues  

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DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/288627.288644
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Charu C. Aggarwal , Joel L. Wolf , Philip S. Yu , Marina Epelman, The S-Tree: An Efficient Index for Multidimensional Objects, Proceedings of the 5th International Symposium on Advances in Spatial Databases, p.350-373, July 15-18, 1997
 
2
Aggarwal C. C., Sun Z., and Yu P. S. Online Generation of Profile Association Rules. Proceedings of the International Conference on Knowledge Discovery and Data Mining, August 1998.
3
Rakesh Agrawal , Tomasz Imieliński , Arun Swami, Mining association rules between sets of items in large databases, Proceedings of the 1993 ACM SIGMOD international conference on Management of data, p.207-216, May 25-28, 1993, Washington, D.C., United States
 
4
Rakesh Agrawal , Ramakrishnan Srikant, Fast Algorithms for Mining Association Rules in Large Databases, Proceedings of the 20th International Conference on Very Large Data Bases, p.487-499, September 12-15, 1994
 
5
Rakesh Agrawal , Ramakrishnan Srikant, Mining Sequential Patterns, Proceedings of the Eleventh International Conference on Data Engineering, p.3-14, March 06-10, 1995
6
Antonin Guttman, R-trees: a dynamic index structure for spatial searching, Proceedings of the 1984 ACM SIGMOD international conference on Management of data, June 18-21, 1984, Boston, Massachusetts
 
7
Jiawei Han , Yongjian Fu, Discovery of Multiple-Level Association Rules from Large Databases, Proceedings of the 21th International Conference on Very Large Data Bases, p.420-431, September 11-15, 1995
 
8
Maurice A. W. Houtsma , Arun N. Swami, Set-Oriented Mining for Association Rules in Relational Databases, Proceedings of the Eleventh International Conference on Data Engineering, p.25-33, March 06-10, 1995
9
Mika Klemettinen , Heikki Mannila , Pirjo Ronkainen , Hannu Toivonen , A. Inkeri Verkamo, Finding interesting rules from large sets of discovered association rules, Proceedings of the third international conference on Information and knowledge management, p.401-407, November 29-December 02, 1994, Gaithersburg, Maryland, United States  [doi>10.1145/191246.191314]
 
10
Brian Lent , Arun N. Swami , Jennifer Widom, Clustering Association Rules, Proceedings of the Thirteenth International Conference on Data Engineering, p.220-231, April 07-11, 1997
 
11
Mannila H., Toivonen H., and Verkamo A. I. Efficient algorithms for discovering association rules. AAAI Workshop on Knowledge Discovery in Databases, pages 181-192, Seattle, Washington, july 1994.
 
12
Raymond T. Ng , Jiawei Han, Efficient and Effective Clustering Methods for Spatial Data Mining, Proceedings of the 20th International Conference on Very Large Data Bases, p.144-155, September 12-15, 1994
13
Jong Soo Park , Ming-Syan Chen , Philip S. Yu, An effective hash-based algorithm for mining association rules, Proceedings of the 1995 ACM SIGMOD international conference on Management of data, p.175-186, May 22-25, 1995, San Jose, California, United States
 
14
Ashoka Savasere , Edward Omiecinski , Shamkant B. Navathe, An Efficient Algorithm for Mining Association Rules in Large Databases, Proceedings of the 21th International Conference on Very Large Data Bases, p.432-444, September 11-15, 1995
 
15
Ramakrishnan Srikant , Rakesh Agrawal, Mining Generalized Association Rules, Proceedings of the 21th International Conference on Very Large Data Bases, p.407-419, September 11-15, 1995
16
Ramakrishnan Srikant , Rakesh Agrawal, Mining quantitative association rules in large relational tables, Proceedings of the 1996 ACM SIGMOD international conference on Management of data, p.1-12, June 04-06, 1996, Montreal, Quebec, Canada
 
17
Hannu Toivonen, Sampling Large Databases for Association Rules, Proceedings of the 22th International Conference on Very Large Data Bases, p.134-145, September 03-06, 1996

CITED BY  4
Fernando Berzal , Juan-Carlos Cubero , Daniel Sánchez , José María Serrano, ART: A Hybrid Classification Model, Machine Learning, v.54 n.1, p.67-92, January 2004
Amit A. Nanavati , Krishna P. Chitrapura , Sachindra Joshi , Raghu Krishnapuram, Mining generalised disjunctive association rules, Proceedings of the tenth international conference on Information and knowledge management, October 05-10, 2001, Atlanta, Georgia, USA
Charu C. Aggarwal , Zheng Sun , Philip S. Yu, Fast Algorithms for Online Generation of Profile Association Rules, IEEE Transactions on Knowledge and Data Engineering, v.14 n.5, p.1017-1028, September 2002
Tamas Abraham, Event sequence mining to develop profiles for computer forensic investigation purposes, Proceedings of the 2006 Australasian workshops on Grid computing and e-research, p.145-153, January 16-19, 2006, Hobart, Tasmania, Australia

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL

Additional Classification:
  G. Mathematics of Computing
  G.4 MATHEMATICAL SOFTWARE
      Subjects: Algorithm design and analysis

  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining


General Terms:
Algorithms, Design, Management, Measurement, Performance, Theory

Collaborative Colleagues:
Charų C. Aggarwal: colleagues
Zheng Sun: colleagues
Philip S. Yu: colleagues

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