Fast Nearest Neighbor Search in Medical Image Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
An ontology engineering methodology for DOGMA
Applied Ontology - Ontological Foundations of Conceptual Modelling
Finding data broadness via generalized nearest neighbors
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
DIY-CDR: an ontology-based, Do-It-Yourself component discoverer and recommender
Personal and Ubiquitous Computing
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The GRASIM (Graph-Aided Similarity calculation) algorithm is designed to solve the problem of ontology-based data matching. We subdivide the matching problem into the ones of restructuring a graph (or a network) and calculating the shortest path between two sub-graphs (or sub-networks). It uses Semantic Decision Tables (SDTs) for storing semantically rich configuration information of the graph. This paper presents an evaluation methodology and the evaluation results while choosing Dijkstra's algorithm to calculate the shortest paths. The tests have been executed with an actual use case of eLearning and training in British Telecom (the Amsterdam branch).