loading
Papers

Research.Publish.Connect.

Paper

Authors: Mamoun Abu Helou 1 and Matteo Palmonari 2

Affiliations: 1 Al-Istiqlal University, Palestinian Territory, Occupied ; 2 University of Milano-Bicocca, Italy

ISBN: 978-989-758-272-1

Keyword(s): Users Feedback, Interactive Mapping, Cross-Lingual Ontology Mapping.

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

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 require d 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. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.134.98

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Abu Helou, Mamoun 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

@conference{keod17,
author={Abu Helou, Mamoun 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},
}

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, Mamoun
AU - Palmonari, M.
PY - 2017
SP - 57
EP - 66
DO - 10.5220/0006503200570066

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.