SemLAV: Querying deep web and linked open data with SPARQL

Pauline Folz*, Gabriela Montoya, Hala Skaf-Molli, Pascal Molli, Maria Esther Vidal


Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

2 Citationer (Scopus)


SemLAV allows to execute SPARQL queries against the Deep Web and Linked Open Data data sources. It implements the mediatorwrapper architecture based on view definitions over remote data sources. SPARQL queries are expressed using a mediator schema vocabulary, and SemLAV selects relevant data sources and rank them. The ranking strategy is designed to deliver results quickly based only on view definitions, i.e., no statistics, nor probing on sources are required. In this demonstration, we validate the effectiveness of SemLAV approach with real data sources from social networks and Linked Open Data. We show in different setups that materializing only a subset of ranked relevant views is enough to deliver significant part of expected results.

TitelThe Semantic Web : ESWC 2014 Satellite Events, Revised Selected Papers
RedaktørerAnna Tordai, Eva Blomqvist, Harald Sack, Raphaël Troncy, Valentina Presutti, Ioannis Papadakis
Antal sider6
Publikationsdato1 jan. 2014
ISBN (Elektronisk)9783319119540
StatusUdgivet - 1 jan. 2014
Begivenhed11th European Semantic Web Symposium on Satellite Events, ESWC 2014 - Ouro Preto, Brasilien
Varighed: 20 okt. 201422 okt. 2014


Konference11th European Semantic Web Symposium on Satellite Events, ESWC 2014
ByOuro Preto
SponsorAnnomarket, Big Data Public-Private Forum, Fluid Operations, Forging Online Education through FIRE (FORGE), iSOCO, LDBC: Linked Data Benchmark Council, LinkedTV, LinkedUp, MediaMixer, PlanetData, Prelida: Preserving Linked Data,, XLike, Yahoo! Labs
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


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