In the last years, the Web has been evolving, trans- forming itself in a semantic Web [1]. The new Web aims at guaranteeing almost completely automatic access to information sources, by introducing ontolo- gies [6, 7, 4] and using mobile agents [8]. Ontolo- gies, representing agents’ knowledge, will allow inte- gration of heterogenous resources to support global information systems. The use of ontologies in agent framework is not an easy task, especially as a mea- surement of ontological similarity. Although several ontology models [3, 2] and several measurements for semantics similarity have been presented in the lit- erature, there is a need for more sensitive measure- ments which can provide a degree of similarity be- tween concepts in order to perform semantic match- ing. Such measurements should take into account the structure of the concepts description and the rela- tionships between concepts. Starting from the graph- oriented model proposed in ONION [10], the present work proposes an algorithm to assess the semantic similarity between two concepts. The resulting data structure is used to represent agent knowledge, while the similarity algorithm compares concepts placed on different agent platforms. The proposed algorithm has been designed for a biological domain and devel- oped for BioAgent [12], a mobile agent platform for distributed biological applications.
An ontology similarity algorithm for BioAgent
MERELLI, Emanuela;CULMONE, Rosario;
2002-01-01
Abstract
In the last years, the Web has been evolving, trans- forming itself in a semantic Web [1]. The new Web aims at guaranteeing almost completely automatic access to information sources, by introducing ontolo- gies [6, 7, 4] and using mobile agents [8]. Ontolo- gies, representing agents’ knowledge, will allow inte- gration of heterogenous resources to support global information systems. The use of ontologies in agent framework is not an easy task, especially as a mea- surement of ontological similarity. Although several ontology models [3, 2] and several measurements for semantics similarity have been presented in the lit- erature, there is a need for more sensitive measure- ments which can provide a degree of similarity be- tween concepts in order to perform semantic match- ing. Such measurements should take into account the structure of the concepts description and the rela- tionships between concepts. Starting from the graph- oriented model proposed in ONION [10], the present work proposes an algorithm to assess the semantic similarity between two concepts. The resulting data structure is used to represent agent knowledge, while the similarity algorithm compares concepts placed on different agent platforms. The proposed algorithm has been designed for a biological domain and devel- oped for BioAgent [12], a mobile agent platform for distributed biological applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
