01822nam a2200229 a 450000100080000000500110000800800410001902000180006010000230007824500840010126003380018549000470052350000690057052008320063965300280147165300190149965300190151865300140153765300130155165300140156470000140157810082652020-01-17       2004    bl uuuu     u00u1 u    #d  a3-540-23662-71 aSOUZA, K. X. S. de  aAligning ontologies and evaluating concept similarities.h[electronic resource]  aIn: OTM CONFEDERATED INTERNATIONAL CONFERENCES, 3.; COOPERATIVE INFORMATION SYSTEMS; DISTRIBUTED OBJECTS AND APPLICATIONS; ONTOLOGIES, DATABASES AND APPLICATIONS OF SEMANTICS, 2014, Agia Napa. On the move to meaningful internet systems 2004: CoopIS, DOA, and ODBASE: proceedings. Berlin: Springer, 2004. part. II, p. 1012-1029.c2004  a(Lecture notes in computer science, 3291).  aEditores: Robert Meersman, Zahir Tari. CoopIS, DOA, ODBASE 2004.  aAbstract. An innate characteristic of the development of ontologies is that they are often created by independent groups of expertise, which generates the necessity of merging and aligning ontologies covering overlapping domains. However, a central issue in the merging process is the evaluation of the differences between two ontologies, viz. the establishment of a similarity measure between their concepts. Many algorithms and tools have been proposed for merging of ontologies, but the majority of them disregard the structural properties of the source ontologies, focusing mostly on syntactic analysis. This article focuses on the alignment of ontologies through Formal Concept Analysis, a data analysis technique founded on lattice theory, and on the use of similarity measures to identify cross-ontology related concepts  aFormal Concept Analysis  aGalois lattice  aLattice theory  aOntologia  aOntology  aThesaurus1 aDAVIS, J.