SEMANTICS-BASED SIMILARITY DECISIONS FOR ONTOLOGIES

Dennis McLeod

Abstract

Many data representation structures, such as web site categories and domain ontologies, have been established for semantic-based information search and retrieval on the web. These structures consist of concepts and their interrelationships. Approaches to determine the similarity in semantics among concepts in data representation structures have been developed in order to facilitate information retrieval and recommendation processes. Some approaches are only suitable for similarity computations in pure tree structures. Other approaches designed for the Directed Acyclic Graph structures yield high computational complexity for online similarity decisions. In order to provide efficient similarity computations for data representation structures, we propose a geometry-based solution. Similarity computations are based on geometric properties. The similarity model is based on the proposed geometry-based solution, and the online similarity computation is performed in a constant time.

References

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Paper Citation


in Harvard Style

McLeod D. (2005). SEMANTICS-BASED SIMILARITY DECISIONS FOR ONTOLOGIES . In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 972-8865-19-8, pages 447-450. DOI: 10.5220/0002554904470450


in Bibtex Style

@conference{iceis05,
author={Dennis McLeod},
title={SEMANTICS-BASED SIMILARITY DECISIONS FOR ONTOLOGIES},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2005},
pages={447-450},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002554904470450},
isbn={972-8865-19-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - SEMANTICS-BASED SIMILARITY DECISIONS FOR ONTOLOGIES
SN - 972-8865-19-8
AU - McLeod D.
PY - 2005
SP - 447
EP - 450
DO - 10.5220/0002554904470450