Feature-based Ontology Mapping from an Information Receivers’ Viewpoint

Fumiko Kano Glückstad, Morten Mørup

Abstract

This paper compares four algorithms for computing feature-based similarities between concepts respectively possessing a distinctive set of features. The eventual purpose of comparing these feature-based similarity algorithms is to identify a candidate term in a Target Language (TL) that can optimally convey the original meaning of a culturally-specific Source Language (SL) concept to a TL audience by aligning two culturally-dependent domain-specific ontologies. The results indicate that the Bayesian Model of Generalization [1] performs best, not only for identifying candidate translation terms, but also for computing probabilities that an information receiver successfully infers the meaning of an SL concept from a given TL translation.

References

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Paper Citation


in Harvard Style

Kano Glückstad F. and Mørup M. (2012). Feature-based Ontology Mapping from an Information Receivers’ Viewpoint . In Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012) ISBN 978-989-8565-16-7, pages 34-43. DOI: 10.5220/0004088200340043


in Bibtex Style

@conference{nlpcs12,
author={Fumiko Kano Glückstad and Morten Mørup},
title={Feature-based Ontology Mapping from an Information Receivers’ Viewpoint},
booktitle={Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012)},
year={2012},
pages={34-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004088200340043},
isbn={978-989-8565-16-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012)
TI - Feature-based Ontology Mapping from an Information Receivers’ Viewpoint
SN - 978-989-8565-16-7
AU - Kano Glückstad F.
AU - Mørup M.
PY - 2012
SP - 34
EP - 43
DO - 10.5220/0004088200340043