Exploiting visual similarities for ontology alignment

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• dc.contributor.author Doulaverakis, Charalamposca
• dc.contributor.author Vrochidis, Stefanosca
• dc.contributor.author Kompatsiaris, Ioannisca
• dc.date.accessioned 2017-02-02T14:26:51Z
• dc.date.available 2017-02-02T14:26:51Z
• dc.date.issued 2015ca
• dc.description.abstract Ontology alignment is the process where two different ontologies that usually describe similar domains are ’aligned’, i.e. a set of correspondences between their entities, regarding semantic equivalence, is determined. In order to identify these correspondences several methods and metrics that measure semantic equivalence have been proposed in literature. The most common features that these metrics employ are string-, lexical-, structure- and semantic-based similarities for which several approaches have been developed. However, what hasn’t been investigated is the usage of visual-based features for determining entity similarity in cases where images are associated with concepts. Nowadays the existence of several resources (e.g. ImageNet) that map lexical concepts onto images allows for exploiting visual similarities for this purpose. In this paper, a novel approach for ontology matching based on visual similarity is presented. Each ontological entity is associated with sets of images, retrieved through ImageNet or web-based search, and state of the art visual feature extraction, clustering and indexing for computing the similarity between entities is employed. An adaptation of a popular Wordnet-based matching algorithm to exploit the visual similarity is also proposed. Our method is compared with traditional metrics against a standard ontology alignment benchmark dataset and demonstrates promising results.en
• dc.description.sponsorship This work was supported by MULTISENSOR (contract no. FP7-610411) and KRISTINA (contract no./nH2020-645012) projects, partially funded by the European Commission.en
• dc.format.mimetype application/pdfca
• dc.identifier.citation Doulaverakis C, Vrochidis S, Kompatsiaris I. Exploiting visual similarities for ontology alignment. In: Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) KEOD; 2015 Nov 12-14; Lisbon, Portugal. Portugal: SCITEPRESS; 2015. vol. 2. p. 29-37. DOI: 10.5220/0005588200290037ca
• dc.identifier.doi http://dx.doi.org/10.5220/0005588200290037
• dc.identifier.uri http://hdl.handle.net/10230/28035
• dc.language.iso engca
• dc.publisher SCITEPRESSca
• dc.relation.ispartof Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) KEOD; 2015 Nov 12-14; Lisbon, Portugal. Portugal: SCITEPRESS; 2015. vol. 2. p. 29-37.en
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/645012
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/610411
• dc.rights © 2015 by SCITEPRESS – Science and Technology Publications, Lda.ca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.subject.keyword ontology alignmenten
• dc.subject.keyword visual similarityen
• dc.subject.keyword imageNeten
• dc.subject.keyword wordneten
• dc.title Exploiting visual similarities for ontology alignmentca
• dc.type info:eu-repo/semantics/conferenceObjectca
• dc.type.version info:eu-repo/semantics/publishedVersionca