Article

Mining Generalized Association Rules

Authors:

Ramakrishnan Srikant,

Rakesh AgrawalAuthors Info & Claims

VLDB '95: Proceedings of the 21th International Conference on Very Large Data Bases

Pages 407 - 419

Published: 11 September 1995 Publication History

Abstract

No abstract available.

References

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[1] Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference 1993: 207-216.

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[2] Rakesh Agrawal, Ramakrishnan Srikant: Fast Algorithms for Mining Association Rules in Large Databases. VLDB 1994: 487-499.

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[3] Noga Alon, Joel Spencer: The Probabilistic Method. John Wiley 1992, ISBN 0-471-53588-5.

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[4] Torben Hagerup, Christine Rüb: A Guided Tour of Chernoff Bounds. Inf. Process. Lett. 33(6): 305-308(1990).

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[5] Maurice A. W. Houtsma, Arun N. Swami: Set-Oriented Mining for Association Rules in Relational Databases. ICDE 1995: 25-33.

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[6] Heikki Mannila, Hannu Toivonen, A. Inkeri Verkamo: Efficient Algorithms for Discovering Association Rules. KDD Workshop 1994: 181-192.

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[7] Jong Soo Park, Ming-Syan Chen, Philip S. Yu: An Effective Hash Based Algorithm for Mining Association Rules. SIGMOD Conference 1995: 175-186.

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[8] Gregory Piatetsky-Shapiro: Discovery, Analysis, and Presentation of Strong Rules. Knowledge Discovery in Databases 1991: 229-248.

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[9] Ramakrishnan Srikant, Rakesh Agrawal: Mining Generalized Association Rules. VLDB 1995: 407-419.

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Thilakaratne MFalkner KAtapattu T(2019)A Systematic Review on Literature-based DiscoveryACM Computing Surveys10.1145/336575652:6(1-34)Online publication date: 10-Dec-2019
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Mining Generalized Association Rules
1. Information systems
  1. Information systems applications

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Published In

VLDB '95: Proceedings of the 21th International Conference on Very Large Data Bases

September 1995

720 pages

ISBN:1558603794

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Morgan Kaufmann Publishers Inc.

San Francisco, CA, United States

Publication History

Published: 11 September 1995

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Preknowledge-based generalized association rules mining

Mining Inter-transactional Association Rules: Generalization and Empirical Evaluation

Efficient Mining of Intertransaction Association Rules

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