Artificial Intelligence: Methodology, Systems, and by Patryk Burek (auth.), Christoph Bussler, Dieter Fensel

By Patryk Burek (auth.), Christoph Bussler, Dieter Fensel (eds.)

The eleventh convention “Artificial Intelligence: technique, platforms, purposes – Semantic net demanding situations” (AIMSA 2004) endured effectively pursuing the most goal of the AIMSA sequence of meetings – to foster the multidisciplinary group of man-made intelligence researchers, embracing either the theoretic underpinnings of the sector and the sensible concerns concerned about improvement, deployment, and upkeep of platforms with clever habit. because the first convention in 1984 AIMSA has supplied an awesome discussion board for foreign clinical alternate among Central/Eastern Europe and the remainder of the realm and it really is much more very important these days within the uni- ing Europe. the present AIMSA version is targeted on Semantic internet tools and applied sciences. the web is altering the typical providers panorama, and how we do issues in virtually each area of our existence. internet providers are quickly turning into the allowing expertise of latest e-business and e-commerce platforms, and may quickly rework the internet because it is now right into a dispensed computation and alertness framework. The rising Semantic internet paradigm delivers to annotate internet artefacts to permit automatic reasoning approximately them. while utilized to e-services, the paradigm hopes to supply gigantic automation for actions corresponding to discovery, invocation, meeting, and tracking of e-services. 100 and seventy-six fascinating papers have been submitted to the conference.

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Additional resources for Artificial Intelligence: Methodology, Systems, and Applications: 11th International Conference, AIMSA 2004, Varna, Bulgaria, September 2-4, 2004. Proceedings

Example text

Therefore, it must be emphasized that although LSI exploits structural information of ontologies and WordNet, it ends up with semantic associa- Capturing Semantics Towards Automatic Coordination of Domain Ontologies 25 tions between terms. Given a query (a concept description), retrieval aims to locate a point in space that is close to the WordNet sense that expresses the intended meaning of this concept. Sm that are the senses of a WordNet lexical entry C’, where C’ is a linguistic variation of a concept C [6].

There exists several measures of similarity between concepts linked by the relation “is a” The relation “is a” is a transitive, asymmetrical relation. The measures presented in [21] and [28] are calculated from the depth of each concept in the ontology. The measure proposed in [28] is more pertinent than the former as it takes into account the structure of the hierarchy by considering the depth of the subsuming (or generalising) concept of the two concepts in question. However, it accepts that the semantic distance between two concepts linked by the relation “is a” is equal whereas this is not necessarily the case.

Landauer T. : Indexing by Latent Semantic Analysis. , Bernstein P. : Generic schema matching with Cupid. : An Algorithm for Matching Contextualized Schemas via SAT. , Pisanelli D. : An Overview of the ONIONS Project: Applying Ontologies to the Integration of Medical Terminologies. Data and Knowledge Engineering, 1999, vol. : FCA-Merge: Bottom-Up Merging of Ontologies. In: B. ): Proc. 17th Intl. Conf. on Artificial Intelligence (IJCAI ’01). : Learning to map between ontologies on the semantic web.

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