research-article

Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds

Authors:

Jerry Chun-Wei Lin,

Philippe Fournier-Viger,

Tzung-Pei HongAuthors Info & Claims

C3S2E '15: Proceedings of the Eighth International C* Conference on Computer Science & Software Engineering

Pages 9 - 17

https://doi.org/10.1145/2790798.2790807

Published: 13 July 2015 Publication History

Abstract

High-utility itemset mining (HUIM) is an emerging topic in data mining. It consists of discovering high-utility itemsets (HUIs), i.e. groups of items (itemsets) that generate a high profit in transactional databases. Several algorithms have been proposed for this task. However, they suffer from an important limitation, which is to rely on a single minimum utility threshold as the sole criterion for identifying HUIs. In this paper, we address this issue by introducing the novel framework of HUIM with multiple minimum utility thresholds (HUIM-MMU). According to this framework, the user may specify different thresholds for each item, to discover HUIs. To perform HUIM-MMU, we first present an algorithm named HUI-MMU, which relies on a new sorted downward closure (SDC) property and least minimum utility threshold (LMU). Furthermore, an improved algorithm, namely HUI-MMUTID, is also proposed based on TID-index strategy, to increase mining performance. Substantial experiments both on real-life and synthetic datasets show that the two proposed algorithms can efficiently and effectively discover the complete set of HUIs in transactional databases while considering multiple minimum utility thresholds.

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Cited By

Nguyen DTran MLe B(2023)A new algorithm using integer programming relaxation for privacy-preserving in utility miningApplied Intelligence10.1007/s10489-023-04913-w53:21(25106-25118)Online publication date: 3-Aug-2023
https://doi.org/10.1007/s10489-023-04913-w
Alhusaini NLi JFournier-Viger PHawbani AChen G(2022)Mining High Utility Itemset with Multiple Minimum Utility Thresholds Based on Utility Deviation2022 IEEE International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW58026.2022.00071(490-496)Online publication date: Nov-2022
https://doi.org/10.1109/ICDMW58026.2022.00071
Saleti SNaga Sahithya NRasagna KHemalatha KSai Charan BKarthik Upendra P(2022)Constraint Pushing Multi-threshold Framework for High Utility Time Interval Sequential Pattern MiningSoft Computing and its Engineering Applications10.1007/978-3-031-05767-0_21(264-273)Online publication date: 7-May-2022
https://doi.org/10.1007/978-3-031-05767-0_21
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Index Terms

Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Other conferences

C3S2E '15: Proceedings of the Eighth International C* Conference on Computer Science & Software Engineering

July 2015

166 pages

ISBN:9781450334198

DOI:10.1145/2790798

General Chair:
Bipin C. Desai
Concordia University, Canada
,
Program Chair:
Motomichi Toyoma
Keio University, Japan

Copyright © 2015 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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Keio University: Keio University
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New York, NY, United States

Publication History

Published: 13 July 2015

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C3S2E 2015

C3S2E 2015: Eighth International C* Conference on Computer Science & Software Engineering

July 13 - 15, 2015

Yokohama, Japan

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Overall Acceptance Rate 12 of 42 submissions, 29%

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Cited By

Nguyen DTran MLe B(2023)A new algorithm using integer programming relaxation for privacy-preserving in utility miningApplied Intelligence10.1007/s10489-023-04913-w53:21(25106-25118)Online publication date: 3-Aug-2023
https://doi.org/10.1007/s10489-023-04913-w
Alhusaini NLi JFournier-Viger PHawbani AChen G(2022)Mining High Utility Itemset with Multiple Minimum Utility Thresholds Based on Utility Deviation2022 IEEE International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW58026.2022.00071(490-496)Online publication date: Nov-2022
https://doi.org/10.1109/ICDMW58026.2022.00071
Saleti SNaga Sahithya NRasagna KHemalatha KSai Charan BKarthik Upendra P(2022)Constraint Pushing Multi-threshold Framework for High Utility Time Interval Sequential Pattern MiningSoft Computing and its Engineering Applications10.1007/978-3-031-05767-0_21(264-273)Online publication date: 7-May-2022
https://doi.org/10.1007/978-3-031-05767-0_21
Saleti STangirala JThirumalaisamy R(2021)Distributed Mining of High Utility Time Interval Sequential Patterns with Multiple Minimum Utility ThresholdsAdvances and Trends in Artificial Intelligence. Artificial Intelligence Practices10.1007/978-3-030-79457-6_8(86-97)Online publication date: 19-Jul-2021
https://doi.org/10.1007/978-3-030-79457-6_8
Zhang CHan MSun RDu SShen M(2020)A Survey of Key Technologies for High Utility Patterns MiningIEEE Access10.1109/ACCESS.2020.29819628(55798-55814)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2981962
Alhusaini NLi JAlhusaini A(2019)FLUI-GrowthProceedings of the 2019 International Conference on Artificial Intelligence and Computer Science10.1145/3349341.3349464(535-541)Online publication date: 12-Jul-2019
https://dl.acm.org/doi/10.1145/3349341.3349464
Gan WLin JFournier-Viger PChao HZhan J(2017)Mining of frequent patterns with multiple minimum supportsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2017.01.00960:C(83-96)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1016/j.engappai.2017.01.009
Lin JYang LFournier-Viger PHong TVoznak M(2017)A binary PSO approach to mine high-utility itemsetsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2106-121:17(5103-5121)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s00500-016-2106-1
Gan WLin JFournier-Viger PChao H(2016)More Efficient Algorithms for Mining High-Utility Itemsets with Multiple Minimum Utility ThresholdsProceedings, Part I, 27th International Conference on Database and Expert Systems Applications - Volume 982710.1007/978-3-319-44403-1_5(71-87)Online publication date: 5-Sep-2016
https://dl.acm.org/doi/10.1007/978-3-319-44403-1_5
Lin JGan WFournier-Viger PHong TTseng V(2015)Mining Potential High-Utility Itemsets over Uncertain DatabasesProceedings of the ASE BigData & SocialInformatics 201510.1145/2818869.2818895(1-6)Online publication date: 7-Oct-2015
https://dl.acm.org/doi/10.1145/2818869.2818895

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