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A new class of constraints for constrained frequent pattern mining

Published: 26 March 2012 Publication History

Abstract

Most of the frequent pattern mining algorithms search for all frequent patterns. However, there are many real-life situations in which users are interested in only some tiny portions of the mined frequent patterns. For mining of constrained frequent patterns, several classes of user constraints---such as anti-monotone constraints---have been proposed and their properties have been exploited. In this paper, we introduce a new class of constraints called mixed monotone constraints. We exploit its property for effective mining of frequent patterns satisfying user constraints that sum both positive and negative numerical values.

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Cited By

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  • (2016)Constrained pattern mining in the new eraKnowledge and Information Systems10.1007/s10115-015-0860-547:3(489-516)Online publication date: 1-Jun-2016
  • (2015)Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data StreamsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXI10.1007/978-3-662-47804-2_6(115-139)Online publication date: 17-Jul-2015
  • (2013)Pushing constraints into data streamsProceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications10.1145/2501221.2501232(79-86)Online publication date: 11-Aug-2013
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  1. A new class of constraints for constrained frequent pattern mining

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    cover image ACM Conferences
    SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing
    March 2012
    2179 pages
    ISBN:9781450308571
    DOI:10.1145/2245276
    • Conference Chairs:
    • Sascha Ossowski,
    • Paola Lecca
    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: 26 March 2012

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    Author Tags

    1. aggregate functions
    2. constraints
    3. data mining
    4. frequent itemset mining
    5. monotonicity
    6. numerical attributes

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    SAC 2012
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    SAC 2012: ACM Symposium on Applied Computing
    March 26 - 30, 2012
    Trento, Italy

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    SAC '12 Paper Acceptance Rate 270 of 1,056 submissions, 26%;
    Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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    Cited By

    View all
    • (2016)Constrained pattern mining in the new eraKnowledge and Information Systems10.1007/s10115-015-0860-547:3(489-516)Online publication date: 1-Jun-2016
    • (2015)Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data StreamsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXI10.1007/978-3-662-47804-2_6(115-139)Online publication date: 17-Jul-2015
    • (2013)Pushing constraints into data streamsProceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications10.1145/2501221.2501232(79-86)Online publication date: 11-Aug-2013
    • (2013)Stream mining of frequent sets with limited memoryProceedings of the 28th Annual ACM Symposium on Applied Computing10.1145/2480362.2480398(173-175)Online publication date: 18-Mar-2013
    • (2013)Pushing Constraints into a Pattern-TreeProceedings of the 10th International Conference on Modeling Decisions for Artificial Intelligence - Volume 823410.1007/978-3-642-41550-0_13(139-151)Online publication date: 20-Nov-2013
    • (2012)A constrained frequent pattern mining system for handling aggregate constraintsProceedings of the 16th International Database Engineering & Applications Sysmposium10.1145/2351476.2351479(14-23)Online publication date: 8-Aug-2012
    • (2012)Mining popular patterns from transactional databasesProceedings of the 14th international conference on Data Warehousing and Knowledge Discovery10.1007/978-3-642-32584-7_24(291-302)Online publication date: 3-Sep-2012

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