research-article

Association rule mining with mostly associated sequential patterns

Author:

Ömer M. SoysalAuthors Info & Claims

Expert Systems with Applications: An International Journal, Volume 42, Issue 5

Pages 2582 - 2592

https://doi.org/10.1016/j.eswa.2014.10.049

Published: 01 April 2015 Publication History

Abstract

Extraction of interesting patterns from data in the form of mostly associated sequential patterns.Speeding up the finding interesting patterns in data.Providing a tool for visual exploration of patterns extracted from data.Ability to be used for searching patterns in big data.The proposed algorithm can be extended to find different type of patterns such as the weakest associated patterns. In this paper, we address the problem of mining structured data to find potentially useful patterns by association rule mining. Different than the traditional find-all-then-prune approach, a heuristic method is proposed to extract mostly associated patterns (MASPs). This approach utilizes a maximally-association constraint to generate patterns without searching the entire lattice of item combinations. This approach does not require a pruning process. The proposed approach requires less computational resources in terms of time and memory requirements while generating a long sequence of patterns that have the highest co-occurrence. Furthermore, k-item patterns can be obtained thanks to the sub-lattice property of the MASPs. In addition, the algorithm produces a tree of the detected patterns; this tree can assist decision makers for visual analysis of data. The outcome of the algorithm implemented is illustrated using traffic accident data. The proposed approach has a potential to be utilized in big data analytics.

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Cited By

Kim YHwangbo HLee HLee W(2024)Sequence aware recommenders for fashion E-commerceElectronic Commerce Research10.1007/s10660-022-09627-824:4(2733-2753)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10660-022-09627-8
Fister IFister IFister DPodgorelec VSalcedo-Sanz S(2023)A comprehensive review of visualization methods for association rule miningExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.120901233:COnline publication date: 15-Dec-2023
https://dl.acm.org/doi/10.1016/j.eswa.2023.120901
Véras DPrudêncio RFerraz C(2019)CD-CARSExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.06.020135:C(388-409)Online publication date: 30-Nov-2019
https://dl.acm.org/doi/10.1016/j.eswa.2019.06.020
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Association rule mining with mostly associated sequential patterns
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cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 42, Issue 5

April 2015

563 pages

ISSN:0957-4174

Issue’s Table of Contents

Copyright © Elsevier Ltd.

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Pergamon Press, Inc.

United States

Publication History

Published: 01 April 2015

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Cited By

Kim YHwangbo HLee HLee W(2024)Sequence aware recommenders for fashion E-commerceElectronic Commerce Research10.1007/s10660-022-09627-824:4(2733-2753)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s10660-022-09627-8
Fister IFister IFister DPodgorelec VSalcedo-Sanz S(2023)A comprehensive review of visualization methods for association rule miningExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.120901233:COnline publication date: 15-Dec-2023
https://dl.acm.org/doi/10.1016/j.eswa.2023.120901
Véras DPrudêncio RFerraz C(2019)CD-CARSExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.06.020135:C(388-409)Online publication date: 30-Nov-2019
https://dl.acm.org/doi/10.1016/j.eswa.2019.06.020
He ZZhang SWu J(2019)Significance-based discriminative sequential pattern miningExpert Systems with Applications: An International Journal10.1016/j.eswa.2018.12.046122:C(54-64)Online publication date: 15-May-2019
https://dl.acm.org/doi/10.1016/j.eswa.2018.12.046
Yadav DChowdary C(2018)OOIMASPExpert Systems with Applications: An International Journal10.1016/j.eswa.2017.10.01593:C(62-71)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1016/j.eswa.2017.10.015
Ilayaraja NMary Magdalene Jane FSafar MNadarajan R(2016)WARM Based Data Pre-fetching and Cache Replacement Strategies for Location Dependent Information System in Wireless EnvironmentWireless Personal Communications: An International Journal10.1007/s11277-016-3425-390:4(1811-1842)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1007/s11277-016-3425-3
Soysal ÖGupta EDonepudi H(2016)A sparse memory allocation data structure for sequential and parallel association rule miningThe Journal of Supercomputing10.1007/s11227-015-1566-x72:2(347-370)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1007/s11227-015-1566-x
Zheng WWang ZHuang HMeng LQiu X(2016)SPSRGCluster Computing10.1007/s10586-016-0633-219:4(1703-1721)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s10586-016-0633-2
Maragatham GLakshmi M(2015)UTARMInternational Journal of Knowledge Engineering and Data Mining10.1504/IJKEDM.2015.0712933:2(208-237)Online publication date: 1-Aug-2015
https://dl.acm.org/doi/10.1504/IJKEDM.2015.071293

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