Design and evaluation of algorithms for image retrieval by spatial similarity
ACM Transactions on Information Systems (TOIS)
Nonparametric methods for quantitative analysis (3rd ed.)
Nonparametric methods for quantitative analysis (3rd ed.)
Metric details for natural-language spatial relations
ACM Transactions on Information Systems (TOIS)
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Toward the semantic geospatial web
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Picture Similarity Retrieval Using the 2D Projection Interval Representation
IEEE Transactions on Knowledge and Data Engineering
Topological Invariants for Lines
IEEE Transactions on Knowledge and Data Engineering
A Distance-Based Approach to Entity Reconciliation in Heterogeneous Databases
IEEE Transactions on Knowledge and Data Engineering
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Similarity of Cardinal Directions
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Metric details of topological line-line relations
International Journal of Geographical Information Science
Assessing similarities of qualitative spatio-temporal relations
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
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Computational similarity assessments over spatial objects are typically decomposed into similarity comparisons of geometric and non-geometric attribute values. Psychological findings have suggested that different types of aggregation functions--for the conversions from the attributes' similarity values to the objects' similarity values--should be used depending on whether the attributes are separable (which reflects perceptual independence) or whether they are integral (which reflects such dependencies among the attributes as typically captured in geometric similarity measures). Current computational spatial similarity methods have ignored the potential impact of such differences, however, treating all attributes and their values homogeneously. Through a comprehensive simulation of spatial similarity queries the impact of psychologically compliant (which recognize groups of integral attributes) vs. deviant (which fail to detect such groups) methods have been studied, comparing the top-10 items of the compliant and deviant ranked lists. We found that only for objects with very small numbers of attributes--no more than two or three attributes for the objects--the explicit recognition of integral attributes is negligible, but the differences between compliant and deviant methods become progressively worse as the percentage of integral attributes increases and the number of groups in which these integral attributes are distributed decreases.