research-article

A clustering-based visualization of colocation patterns

Authors:

Frédéric Flouvat,

Nazha Selmaoui-FolcherAuthors Info & Claims

IDEAS '11: Proceedings of the 15th Symposium on International Database Engineering & Applications

Pages 70 - 78

https://doi.org/10.1145/2076623.2076633

Published: 21 September 2011 Publication History

Abstract

Extraction of interesting colocations in geo-referenced data is one of the major tasks in spatial pattern mining. The goal is to find sets of spatial object-types with instances located in the same neighborhood. In this context, the main drawback is the visualization and interpretation of extracted patterns by domain experts. Indeed, common textual representation of colocations loses important spatial information such as the position, the orientation or the spatial distribution of the patterns. To overcome this problem, we propose a new clustering-based visualization technique deeply integrated in the colocation mining algorithm. This new simple, concise and intuitive cartographic visualization considers both spatial information and expert practices. This proposition has been integrated in a Geographic Information System and experimented on a real-world geological data set. Domain experts confirm the added-value of this visualization approach.

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Cited By

Bellinger CJabbar MWine ONielsen CSerrano-Lomelin JOsornio-Vargas AZaïane O(2021)AI Applied to Air Pollution and Environmental Health: A Case Study on Hypothesis GenerationHumanity Driven AI10.1007/978-3-030-72188-6_10(195-222)Online publication date: 2-Dec-2021
https://doi.org/10.1007/978-3-030-72188-6_10
Flouvat FVan Soc JDesmier ESelmaoui-Folcher N(2015)Domain-driven co-location miningGeoinformatica10.1007/s10707-014-0209-319:1(147-183)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1007/s10707-014-0209-3
Akbari MSamadzadegan FWeibel R(2015)A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollutionJournal of Geographical Systems10.1007/s10109-015-0216-417:3(249-274)Online publication date: 25-Jun-2015
https://doi.org/10.1007/s10109-015-0216-4
Show More Cited By

Index Terms

A clustering-based visualization of colocation patterns
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Other conferences

IDEAS '11: Proceedings of the 15th Symposium on International Database Engineering & Applications

September 2011

274 pages

ISBN:9781450306270

DOI:10.1145/2076623

General Chair:
Bipin C. Desai
Concordia University
,
Program Chairs:
Isabel Cruz
University of Illinois at Chicago
,
Jorge Bernardino
Instituto Politecnico de Coimbra

Copyright © 2011 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2011

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French contract

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IDEAS '11

IDEAS '11: 15th International Database Engineering & Applications Symposium

September 21 - 23, 2011

Lisboa, Portugal

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Overall Acceptance Rate 74 of 210 submissions, 35%

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Cited By

Bellinger CJabbar MWine ONielsen CSerrano-Lomelin JOsornio-Vargas AZaïane O(2021)AI Applied to Air Pollution and Environmental Health: A Case Study on Hypothesis GenerationHumanity Driven AI10.1007/978-3-030-72188-6_10(195-222)Online publication date: 2-Dec-2021
https://doi.org/10.1007/978-3-030-72188-6_10
Flouvat FVan Soc JDesmier ESelmaoui-Folcher N(2015)Domain-driven co-location miningGeoinformatica10.1007/s10707-014-0209-319:1(147-183)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1007/s10707-014-0209-3
Akbari MSamadzadegan FWeibel R(2015)A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollutionJournal of Geographical Systems10.1007/s10109-015-0216-417:3(249-274)Online publication date: 25-Jun-2015
https://doi.org/10.1007/s10109-015-0216-4
Leung CTanbeer SBudhia BZacharias LDesai BPokorny JBernardino J(2012)Mining probabilistic datasets verticallyProceedings of the 16th International Database Engineering & Applications Sysmposium10.1145/2351476.2351500(199-204)Online publication date: 8-Aug-2012
https://dl.acm.org/doi/10.1145/2351476.2351500
Leung CJiang FSun LWang YDesai BPokorny JBernardino J(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
https://dl.acm.org/doi/10.1145/2351476.2351479
Sengstock CGertz MVan Canh T(2012)Spatial Interestingness Measures for Co-location Pattern MiningProceedings of the 2012 IEEE 12th International Conference on Data Mining Workshops10.1109/ICDMW.2012.116(821-826)Online publication date: 10-Dec-2012
https://dl.acm.org/doi/10.1109/ICDMW.2012.116

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