research-article

High average-utility itemsets mining: a survey

Authors:

Bhaskar BiswasAuthors Info & Claims

Applied Intelligence, Volume 52, Issue 4

Pages 3901 - 3938

https://doi.org/10.1007/s10489-021-02611-z

Published: 01 March 2022 Publication History

Abstract

HUIM (High utility itemsets mining) is a sub-division of data mining dealing with the task to obtain promising patterns in the quantitative datasets. A variant of HUIM is to discover the HAUIM (High average-utility itemsets mining) where average-utility measure is used to obtain the utility of itemsets. HAUIM is the refined version of FIM (Frequent itemset mining) problem and has various applications in the field of market basket analysis, bio-informatics, text mining, network traffic analysis, product recommendation and e-learning among others. In this paper, we provide a comprehensive survey of the state-of-the-art methods of HAUIM to mine the HAUIs (High average-utility itemsets) from the static and dynamic datasets since the induction of the HAUIM problem. We discuss the pros and cons of each category of mining approaches in detail. The taxonomy of HAUIM is presented according to the mining approaches. Finally,various extensions, future directions and research opportunities of HAUIM algorithms are discussed.

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Duong HPham HTruong TFournier-Viger P(2024)Efficient algorithms to mine concise representations of frequent high utility occupancy patternsApplied Intelligence10.1007/s10489-024-05296-254:5(4012-4042)Online publication date: 1-Mar-2024
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Hong THung WTsai YHuang W(2023)Maintenance of High Fuzzy Utility Itemsets Using the Pre-Large-Itemset Concept and Tree StructureProceedings of the 10th Multidisciplinary International Social Networks Conference10.1145/3624875.3624895(118-123)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1145/3624875.3624895
Liu XChen GWu FWen SZuo W(2023)Mining top-k high average-utility itemsets based on breadth-first searchApplied Intelligence10.1007/s10489-023-05076-453:23(29319-29337)Online publication date: 1-Dec-2023
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Index Terms

High average-utility itemsets mining: a survey
1. Computing methodologies
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image Applied Intelligence

Applied Intelligence Volume 52, Issue 4

Mar 2022

1262 pages

ISSN:0924-669X

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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.

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Kluwer Academic Publishers

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Published: 01 March 2022

Accepted: 11 June 2021

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Cited By

Duong HPham HTruong TFournier-Viger P(2024)Efficient algorithms to mine concise representations of frequent high utility occupancy patternsApplied Intelligence10.1007/s10489-024-05296-254:5(4012-4042)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s10489-024-05296-2
Hong THung WTsai YHuang W(2023)Maintenance of High Fuzzy Utility Itemsets Using the Pre-Large-Itemset Concept and Tree StructureProceedings of the 10th Multidisciplinary International Social Networks Conference10.1145/3624875.3624895(118-123)Online publication date: 4-Sep-2023
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https://dl.acm.org/doi/10.1007/s10489-023-05076-4
Cheng ZFang WShen WLin JYuan B(2023)An efficient utility-list based high-utility itemset mining algorithmApplied Intelligence10.1007/s10489-022-03850-453:6(6992-7006)Online publication date: 1-Mar-2023
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Wang HWei JWang XLi XJiang H(2022)IHUMN: an improved high-utility itemsets mining algorithm with negative utility itemsProceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence10.1145/3579654.3579766(1-5)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3579654.3579766

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