Artificial Intelligence: Methodology, Systems, and by Bussler Ch. (Ed), Fensel D. (Ed)

By Bussler Ch. (Ed), Fensel D. (Ed)

This booklet constitutes the refereed complaints of the eleventh foreign convention on man made Intelligence: technique, structures, and purposes, AIMSA 2004, held in Varna, Bulgaria in September 2004.The fifty two revised complete papers offered have been rigorously reviewed and chosen from 176 submissions. The papers are equipped in topical sections on ontology engineering, semantic internet prone, wisdom illustration and processing, laptop studying and information mining, usual language processing, tender computing, neural networks, e-learning structures, multiagent platforms, trend attractiveness, clever choice making, and knowledge retrieval.

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Extra info for Artificial Intelligence: Methodology, Systems, and Applications: 11th International Conference, Aimsa 2004, Varna, Bulgaria, September 2-4, 2004, Proceedings

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Keywords: Ontology mapping, Ontology merging, Latent Semantic Indexing 1 Introduction Ontologies have been realized as the key technology to shaping and exploiting information for the effective management of knowledge and for the evolution of the Semantic Web and its applications. In such a distributed setting, ontologies establish a common vocabulary for community members to interlink, combine, and communicate knowledge shaped through practice and interaction, binding the knowledge processes of creating, importing, capturing, retrieving, and using knowledge.

The ontologies of astronomy also includes the relation “part of” and “is related to”. Mereology, which studies the relations “part of” and “whole of” plays an important role in ontologies. Studies generally recognized that these relations were transitive. However, Winston et al [26] have shown that this is not always the case as these relations do not represent a type of relation but a family of relations: componentobject (pedal-bicycle), member-collection (tree-forest), portion-mass (slice-cake) matter-object (steel-bicycle), characteristic-object (pay-go shopping), place-region (oasis-desert).

In such a setting where different conceptualizations of the same domain exist, information services must effectively answer queries bridging the gaps between their formal ontologies and users’ own conceptualizations. Towards this target, networks of semantically related information must be created at-request. e. mapping, alignment, merging) of ontologies is a major challenge for bridging the gaps between agents (software and human) with different conceptualizations. C. Bussler and D. ): AIMSA 2004, LNAI 3192, pp.

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