Efficient algorithms for finding maximum matching in graphs
ACM Computing Surveys (CSUR)
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Structural similarity in geographical queries to improve query answering
Proceedings of the 2007 ACM symposium on Applied computing
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
GeoPQL: a geographical pictorial query language that resolves ambiguities in query interpretation
Journal on Data Semantics III
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In the Geographic Information System (GIS) domain the evaluation of similarity among geographical objects plays an important role. This paper proposes an approach based on semantic and structural similarities to provide more flexible matches between the query search condition expressed by the user and the possible answers provided by the system. The relaxation model considers with different weights the semantic similarity of geographical concepts, that is evaluated by adopting the information content approach, and the structural similarity of the attributes and types of geographical objects that is inspired by the maximum weighted matching problem in bipartite graphs. The aim of the proposed methodology is to relax structural query constraints, in order to obtain meaningful answers for imprecise or missing data.