HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Handling Spatial Relations in Logical Concept Analysis To Explore Geographical Data

Olivier Bedel 1 Sébastien Ferré 1, * Olivier Ridoux 1
* Corresponding author
1 LIS - Logical Information Systems
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Because of the expansion of geo-positioning tools and the democratization of geographical information, the amount of geo-localized data that is available around the world keeps increasing. So, the ability to efficiently retrieve informations in function of their geographical facet is an important issue. In addition to individual properties such as position and shape, spatial relations between objects are an important criteria for selecting and reaching objects of interest: e.g., given a set of touristic points, selecting those having a nearby hotel or reaching the nearby hotels. In this paper, we propose Logical Concept Analysis (LCA) and its handling of relations for representing and reasoning on various kinds of spatial relations: e.g., Euclidean distance, topological relations. Furthermore, we present an original way of navigating in geolocalized data, and compare the benefits of our approach with traditional Geographical Information Systems (GIS).
Document type :
Conference papers
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download

https://hal.inria.fr/inria-00363592
Contributor : Sébastien Ferré Connect in order to contact the contributor
Submitted on : Monday, February 23, 2009 - 5:38:27 PM
Last modification on : Tuesday, October 19, 2021 - 11:58:50 PM
Long-term archiving on: : Tuesday, June 8, 2010 - 9:03:27 PM

File

icfca2008-bedel.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00363592, version 1

Citation

Olivier Bedel, Sébastien Ferré, Olivier Ridoux. Handling Spatial Relations in Logical Concept Analysis To Explore Geographical Data. Int. Conf. Formal Concept Analysis, 2008, Montreal, Canada. pp.241--257. ⟨inria-00363592⟩

Share

Metrics

Record views

123

Files downloads

148