Multi-user Feedback for Large-scale Cross-lingual Ontology Matching

Mamoun Abu Helou, Matteo Palmonari

2017

Abstract

Automatic matching systems are introduced to reduce the manual workload of users that need to align two ontologies by finding potential mappings and determining which ones should be included in a final alignment. Mappings found by fully automatic matching systems are neither correct nor complete when compared to gold standards. In addition, automatic matching systems may not be able to decide which one, among a set of candidate target concepts, is the best match for a source concept based on the available evidence. To handle the above mentioned problems, we present an interactive mapping Web tool named ICLM (Interactive Cross-lingual Mapping), which aims to improve an alignment computed by an automatic matching system by incorporating the feedback of multiple users. Users are asked to validate mappings computed by the automatic matching system by selecting the best match among a set of candidates, i.e., by performing a mapping selection task. ICLM tries to reduce users’ effort required to validate mappings. ICLM distributes the mapping selection tasks to users based on the tasks’ difficulty, which is estimated by considering the lexical characterization of the ontology concepts, and the confidence of automatic matching algorithms. Accordingly, ICLM estimates the effort (number of users) needed to validate the mappings. An experiment with several users involved in the alignment of large lexical ontologies is discussed in the paper, where different strategies for distributing the workload among the users are evaluated. Experimental results show that ICLM significantly improves the accuracy of the final alignment using the strategies proposed to balance and reduce the user workload.

Paper Citation

in Harvard Style

Abu Helou M. and Palmonari M. (2017). Multi-user Feedback for Large-scale Cross-lingual Ontology Matching.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 57-66. DOI: 10.5220/0006503200570066

in Bibtex Style

@conference{keod17,
author={Mamoun Abu Helou and Matteo Palmonari},
title={Multi-user Feedback for Large-scale Cross-lingual Ontology Matching},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,},
year={2017},
pages={57-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006503200570066},
isbn={978-989-758-272-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - Multi-user Feedback for Large-scale Cross-lingual Ontology Matching
SN - 978-989-758-272-1
AU - Abu Helou M.
AU - Palmonari M.
PY - 2017
SP - 57
EP - 66
DO - 10.5220/0006503200570066