Article

HYPE: mining hierarchical sequential patterns

Authors:

Marc Plantevit,

Maguelonne TeisseireAuthors Info & Claims

DOLAP '06: Proceedings of the 9th ACM international workshop on Data warehousing and OLAP

Pages 19 - 26

https://doi.org/10.1145/1183512.1183518

Published: 10 November 2006 Publication History

Abstract

Mining data warehouses is still an open problem as few approaches really take the specificities of this framework into account (e.g. multidimensionality, hierarchies, historized data). Multidimensional sequential patterns have been studied but they do not provide any way to handle hierarchies. In this paper, we propose an original sequential pattern extraction method that takes the hierarchies into account. This method extracts more accurate knowledge and extends our preceding M²SP approach. We define the concepts related to our problems as well as the associated algorithms. The results of our experiments confirm the relevance of our proposal.

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Cited By

Ribeiro JFontes TSoares CBorges J(2024)Multidimensional subgroup discovery on event logsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123205246:COnline publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123205
Kontarinis AZeitouni KMarinica CVodislav DKotzinos D(2021)Towards a semantic indoor trajectory model: application to museum visitsGeoInformatica10.1007/s10707-020-00430-xOnline publication date: 5-Mar-2021
https://doi.org/10.1007/s10707-020-00430-x
Zhang CDu ZZu Y(2020)An Efficient Algorithm for Extracting High-Utility Hierarchical Sequential PatternsWireless Communications & Mobile Computing10.1155/2020/88162282020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/8816228
Show More Cited By

Index Terms

HYPE: mining hierarchical sequential patterns
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

DOLAP '06: Proceedings of the 9th ACM international workshop on Data warehousing and OLAP

November 2006

110 pages

ISBN:1595935304

DOI:10.1145/1183512

General Chair:
Il-Yeol Song
Drexel University
,
Program Chair:
Panos Vassiliadis
University of Ioannina, Greece

Copyright © 2006 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: 10 November 2006

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CIKM06

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CIKM06: Conference on Information and Knowledge Management

November 10, 2006

Virginia, Arlington, USA

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Overall Acceptance Rate 29 of 79 submissions, 37%

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Cited By

Ribeiro JFontes TSoares CBorges J(2024)Multidimensional subgroup discovery on event logsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123205246:COnline publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123205
Kontarinis AZeitouni KMarinica CVodislav DKotzinos D(2021)Towards a semantic indoor trajectory model: application to museum visitsGeoInformatica10.1007/s10707-020-00430-xOnline publication date: 5-Mar-2021
https://doi.org/10.1007/s10707-020-00430-x
Zhang CDu ZZu Y(2020)An Efficient Algorithm for Extracting High-Utility Hierarchical Sequential PatternsWireless Communications & Mobile Computing10.1155/2020/88162282020Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1155/2020/8816228
Beedkar KGemulla RSellis TDavidson SIves Z(2015)LASHProceedings of the 2015 ACM SIGMOD International Conference on Management of Data10.1145/2723372.2723724(491-503)Online publication date: 27-May-2015
https://dl.acm.org/doi/10.1145/2723372.2723724
Kinnebrew JSegedy JBiswas G(2014)Analyzing the temporal evolution of students’ behaviors in open-ended learning environmentsMetacognition and Learning10.1007/s11409-014-9112-49:2(187-215)Online publication date: 1-Mar-2014
https://doi.org/10.1007/s11409-014-9112-4
Plantevit MLaurent ALaurent DTeisseire MChoong Y(2010)Mining multidimensional and multilevel sequential patternsACM Transactions on Knowledge Discovery from Data10.1145/1644873.16448774:1(1-37)Online publication date: 18-Jan-2010
https://dl.acm.org/doi/10.1145/1644873.1644877
Pitman AZanker M(2010)Insights from Applying Sequential Pattern Mining to E-commerce Click Stream DataProceedings of the 2010 IEEE International Conference on Data Mining Workshops10.1109/ICDMW.2010.31(967-975)Online publication date: 13-Dec-2010
https://dl.acm.org/doi/10.1109/ICDMW.2010.31
Plantevit MLaurent ATeisseire M(2009)Mining convergent and divergent sequences in multidimensional dataInternational Journal of Business Intelligence and Data Mining10.1504/IJBIDM.2009.0290744:3/4(242-266)Online publication date: 1-Nov-2009
https://dl.acm.org/doi/10.1504/IJBIDM.2009.029074
Huang T(2009)Developing an efficient knowledge discovering model for mining fuzzy multi-level sequential patterns in sequence databasesFuzzy Sets and Systems10.1016/j.fss.2009.06.003160:23(3359-3381)Online publication date: 1-Dec-2009
https://dl.acm.org/doi/10.1016/j.fss.2009.06.003
Kazienko P(2008)Mining Sequential Patterns with Negative ConclusionsProceedings of the 10th international conference on Data Warehousing and Knowledge Discovery10.1007/978-3-540-85836-2_40(423-432)Online publication date: 2-Sep-2008
https://dl.acm.org/doi/10.1007/978-3-540-85836-2_40
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