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Authors: Alexandre Gouveia 1 ; Nuno Silva 1 and Paulo Martins 2

Affiliations: 1 Polytechnic of Porto, Portugal ; 2 University of Trás-os-Montes e Alto Douro and Polytechnic of Porto, Portugal

Keyword(s): Ontology Alignment, Information Integration, Rule-based System.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontology Matching and Alignment ; Symbolic Systems

Abstract: Ontology matchers establish correspondences between ontologies to enable knowledge from different sources and domains to be used in ontology mediation tasks (e.g. data transformation and information/ knowledge integration) in many ways. While these processes demand great quality alignments, even the best-performing alignment needs to be corrected and completed before application. In this paper, we propose a rule-based system that improves and completes the automatically-generated alignments into fully-fledged alignments. For that, the rules capture the pre-conditions (existing facts) and the actions to solve each (ambiguous) scenario, in which automatic decisions supported by a folksonomy-based matcher are adopted. The evaluation of the proposed system shows the increasing accuracy of the alignments.

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Paper citation in several formats:
Gouveia, A.; Silva, N. and Martins, P. (2017). Rule-based System Enriched with a Folksonomy-based Matcher for Generating Information Integration Alignments. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD; ISBN 978-989-758-272-1; ISSN 2184-3228, SciTePress, pages 211-218. DOI: 10.5220/0006505302110218

@conference{keod17,
author={Alexandre Gouveia. and Nuno Silva. and Paulo Martins.},
title={Rule-based System Enriched with a Folksonomy-based Matcher for Generating Information Integration Alignments},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD},
year={2017},
pages={211-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006505302110218},
isbn={978-989-758-272-1},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD
TI - Rule-based System Enriched with a Folksonomy-based Matcher for Generating Information Integration Alignments
SN - 978-989-758-272-1
IS - 2184-3228
AU - Gouveia, A.
AU - Silva, N.
AU - Martins, P.
PY - 2017
SP - 211
EP - 218
DO - 10.5220/0006505302110218
PB - SciTePress

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