Estimating query rewriting quality over LOD

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dc.contributor.authorAnai, Torre Bastida
dc.contributor.authorBermadez, Jesas
dc.contributor.authorIllarramendi, Arantza
dc.contributor.institutionHPA
dc.date.accessioned2024-07-24T12:08:28Z
dc.date.available2024-07-24T12:08:28Z
dc.date.issued2019
dc.descriptionPublisher Copyright: © 2019-IOS Press and the authors. All rights reserved.
dc.description.abstractNowadays it is becoming increasingly necessary to query data stored in different datasets of public access, such as those included in the Linked Data environment, in order to get as much information as possible on distinct topics. However, users have difficulty to query those datasets with different vocabularies and data structures. For this reason it is interesting to develop systems that can produce on demand rewritings of queries. Moreover, a semantics preserving rewriting cannot often be guaranteed by those systems due to heterogeneity of the vocabularies. It is at this point where the quality estimation of the produced rewriting becomes crucial. In this paper we present a novel framework that, given a query written in the vocabulary the user is more familiar with, the system rewrites the query in terms of the vocabulary of a target dataset. Moreover, it informs about the quality of the rewritten query with two scores: a similarity factor which is based on the rewriting process itself, and a quality score offered by a predictive model. This Machine Learning based model learns from a set of queries and their intended (gold standard) rewritings. The feasibility of the framework has been validated in a real scenario.en
dc.description.statusPeer reviewed
dc.format.extent26
dc.identifier.citationAnai , T B , Bermadez , J & Illarramendi , A 2019 , ' Estimating query rewriting quality over LOD ' , Semantic Web , vol. 10 , no. 3 , pp. 529-554 . https://doi.org/10.3233/SW-180311
dc.identifier.doi10.3233/SW-180311
dc.identifier.issn1570-0844
dc.identifier.urihttps://hdl.handle.net/11556/3871
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85064091727&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofSemantic Web
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsLinked Open Data
dc.subject.keywordsquery rewriting
dc.subject.keywordsSemantic web
dc.subject.keywordssimilarity
dc.subject.keywordsSPARQL
dc.subject.keywordsInformation Systems
dc.subject.keywordsComputer Science Applications
dc.subject.keywordsComputer Networks and Communications
dc.titleEstimating query rewriting quality over LODen
dc.typejournal article
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