Paper Info
Title
A semantic similarity model for mapping between evolving geospatial data cubes
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 time This paper proposes a semantic similarity model redefined from a model 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 The proposed model has been applied to a set of specifications from different inventory in Montmorency Forest in 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 SOLAP tools as future works.
Year
DOI
Venue
2006
10.1007/11915072_72
OTM Workshops (2)
Keywords
Field
DocType
multidimensional databases,different inventory,multidimensional structure,original model,multidimensional geospatial databases,different hierarchical level,geospatial data cube,different time,semantic similarity model,different version,geospatial data,ontology,multidimensional database,semantic similarity,ontology mapping,data cube
Semantic similarity,Geospatial analysis,Data warehouse,Similitude,Data mining,Information retrieval,Computer science,Precision and recall,Temporal database,Online analytical processing,Data cube
Conference
Volume
ISSN
ISBN
4278
0302-9743
3-540-48273-3
Citations 
PageRank 
References 
3
0.40
15
Authors
3
Name
Order
Citations
PageRank
Mohamed Bakillah116111.55
Mir Abolfazl Mostafavi214416.75
Yvan Bédard320222.80