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Efficiently mining long patterns from databases

Author:

Roberto J. Bayardo, Jr.Authors Info & Claims

SIGMOD '98: Proceedings of the 1998 ACM SIGMOD international conference on Management of data

Pages 85 - 93

https://doi.org/10.1145/276304.276313

Published: 01 June 1998 Publication History

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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Cited By

Sadeequllah MRauf ARehman SAlnazzawi N(2024)Quick mining in dense data: applying probabilistic support prediction in depth-first orderPeerJ Computer Science10.7717/peerj-cs.233410(e2334)Online publication date: 4-Oct-2024
https://doi.org/10.7717/peerj-cs.2334
Barun MÖnder E(2024)Unlocking the Multidisciplinary Potential of Data Science: Insights from Apriori AnalysisJournal of Polytechnic10.2339/politeknik.1432158(1-1)Online publication date: 12-Sep-2024
https://doi.org/10.2339/politeknik.1432158
Wang YLi KLuo YLi GGuo YWang Z(2024)Fast, Robust and Interpretable Participant Contribution Estimation for Federated Learning2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00182(2298-2311)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00182
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Index Terms

Efficiently mining long patterns from databases
1. Information systems
  1. Information systems applications
    1. Data mining
2. Mathematics of computing
  1. Mathematical software

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Published In

cover image ACM Conferences

SIGMOD '98: Proceedings of the 1998 ACM SIGMOD international conference on Management of data

June 1998

599 pages

ISBN:0897919955

DOI:10.1145/276304

Chairmen:
Laura Haas
IBM AlmadenResearch Center, San Jose, CA
,
Pamela Drew
Boeing Co.
,
Editors:
Ashutosh Tiwary
Boeing Co.; and Univ. of Washington, Seattle
,
Michael Franklin
Univ. of Maryland, College Park

ACM SIGMOD Record Volume 27, Issue 2
June 1998
595 pages
ISSN:0163-5808
DOI:10.1145/276305
Chairmen:
Laura Haas
IBM Almaden Research Center, San Jose, CA
,
Pamela Drew
Boeing Co.
,
Editor:
Ashutosh Tiwary
Boeing Co.; and Univ. of Washington, Seattle
Issue’s Table of Contents

Copyright © 1998 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 June 1998

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SIGMOD/PODS98

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SIGMOD/PODS98: Special Interest Group on Management of Data

June 1 - 4, 1998

Washington, Seattle, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Sadeequllah MRauf ARehman SAlnazzawi N(2024)Quick mining in dense data: applying probabilistic support prediction in depth-first orderPeerJ Computer Science10.7717/peerj-cs.233410(e2334)Online publication date: 4-Oct-2024
https://doi.org/10.7717/peerj-cs.2334
Barun MÖnder E(2024)Unlocking the Multidisciplinary Potential of Data Science: Insights from Apriori AnalysisJournal of Polytechnic10.2339/politeknik.1432158(1-1)Online publication date: 12-Sep-2024
https://doi.org/10.2339/politeknik.1432158
Wang YLi KLuo YLi GGuo YWang Z(2024)Fast, Robust and Interpretable Participant Contribution Estimation for Federated Learning2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00182(2298-2311)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00182
Gudyś ASikora MWróbel Ł(2024)Separate and conquer heuristic allows robust mining of contrast sets in classification, regression, and survival dataExpert Systems with Applications10.1016/j.eswa.2024.123376248(123376)Online publication date: Aug-2024
https://doi.org/10.1016/j.eswa.2024.123376
He CChen XChen GGan WFournier-Viger P(2024)Mining credible attribute rules in dynamic attributed graphsExpert Systems with Applications10.1016/j.eswa.2023.123012246(123012)Online publication date: Jul-2024
https://doi.org/10.1016/j.eswa.2023.123012
Bennai SAmroun KLoudni S(2024)New Methods for Compressing Table ConstraintsAdvances in Knowledge Discovery and Management10.1007/978-3-031-40403-0_1(1-28)Online publication date: 1-Feb-2024
https://doi.org/10.1007/978-3-031-40403-0_1
Lan TGuo L(2023)Discovery of User Groups Densely Connecting Virtual and Physical Worlds in Event-Based Social NetworksInternational Journal of Information Technologies and Systems Approach10.4018/IJITSA.32700416:2(1-23)Online publication date: 28-Jul-2023
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Agarwal A(2023)Automating Decision-Making for Hiring Brilliant People While Taking Risk Factors Into Account: A Data Mining Approach2023 International Conference on Disruptive Technologies (ICDT)10.1109/ICDT57929.2023.10150667(293-296)Online publication date: 11-May-2023
https://doi.org/10.1109/ICDT57929.2023.10150667
Pirmoradi SHosseiniyan Khatibi SZununi Vahed SHomaei Rad HKhamaneh AAkbarpour ZSeyedrezazadeh ETeshnehlab MChapman KAnsarin K(2023)Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining methodScientific Reports10.1038/s41598-023-42581-513:1Online publication date: 16-Sep-2023
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Toivonen H(2023)Frequent PatternEncyclopedia of Machine Learning and Data Science10.1007/978-1-4899-7502-7_106-1(1-6)Online publication date: 12-Apr-2023
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