Domain-driven co-location mining: Extraction, visualization and integration in a GIS

Co-location mining is a classical problem in spatial pattern mining. Considering a set of boolean spatial features, the goal is to find subsets of features frequently located together. It has wide applications in environmental management, public safety, transportation or tourism. These last years, m...

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Bibliographic Details
Published in:GeoInformatica 2015-01, Vol.19 (1), p.147-183
Main Authors: Flouvat, Frédéric, Van Soc, Jean-François N’guyen, Desmier, Elise, Selmaoui-Folcher, Nazha
Format: Article
Language:English
Subjects:
Algorithms
Cartography
Computer Science
Data mining
Data Structures and Information Theory
Earth and Environmental Science
Environmental management
Extraction
Geographic information systems
Geographical Information Systems/Cartography
Geography
Geospatial data
Information Storage and Retrieval
Mining
Multimedia Information Systems
Proposals
Remote sensing
Satellite navigation systems
Soil erosion
Visualization
Visualization (Computers)
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Summary:Co-location mining is a classical problem in spatial pattern mining. Considering a set of boolean spatial features, the goal is to find subsets of features frequently located together. It has wide applications in environmental management, public safety, transportation or tourism. These last years, many algorithms have been proposed to extract frequent co-locations. However, most solutions do a “data-centered knowledge discovery” instead of a “expert-centered knowledge discovery”. Successfully providing useful and interpretable patterns to experts is still an open problem. In this setting, we propose a domain-driven co-location mining approach that combines constraint-based mining and cartographic visualization. Experts can push new domain constraints into the mining algorithm, resulting in more relevant patterns and more efficient extraction. Then, they can visualize solutions using a new concise and intuitive cartographic visualization of co-locations. Using this original visualization approach, they identify new interesting patterns, and use uninteresting ones to define new constraints and refine their analysis. These proposals have been integrated into a prototype based on PostGIS geographic information system. Experiments have been done using a real geological datasets studying soil erosion, and results have been validated by a domain expert.
ISSN:1384-6175
1573-7624
DOI:10.1007/s10707-014-0209-3