Sommaire de la publication

Sommaire de la publication

Bakillah, M., M. Mostafavi, Y. BĂ©dard, 2006, A semantic similarity model for mapping between evolving geospatial data cubes, International Workshop on Semantic-based Geographical Information Systems (SeBGIS’06), October 29th – November 3rd, Montpellier, France

Abstract

In a decision-making context, multidimensional geospatial databases are very important. They often represent data coming from heterogeneous and evolving sources. Evolution of multidimensional structures makes difficult, even
impossible answering to temporal queries, because of the lack of relationships between different versions of spatial
cubes created at different periods of time. This paper proposes a semantic similarity model redefined from a model
generally applied in the ontological field to establish semantic relations between data cubes. The proposed model
integrates several types of similarity components adapted to different hierarchical levels of dimensions in
multidimensional databases and also integrates similarity between features of concepts. This allows producing a more
precise evaluation of the similarity. The proposed model has been applied to a set of specifications from different
periods of time in Montmorency Forest in Quebec, Canada. Results show that the proposed model improves precision
and recall compared to the original model. Finally, further investigation is suggested in order to integrate the proposed
model to the existing OLAP and SOLAP tools as future works.