OptiqueVQS swMATH ID: 26466 Software Authors: A. Soylu; M. Giese; E. Jiménez-Ruiz; G. Vega-Gorgojo; I. Horrocks Description: OptiqueVQS: Ontology-based Visual Querying. Visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. In this paper, we demonstrate an ontology-based visual query system, namely OptiqueVQS, which we have been developing for end users within a large industrial project. Homepage: https://pdfs.semanticscholar.org/2903/d0621bdd7cdc68df8852848ff91bee72c16e.pdf Related Software: SPARQL; word2vec; R2RML; RDF123; QueryVOWL; LODeX; ViziQuer; NITELIGHT; iSPARQL; SPARQLGraph; Colt; SemTK; RDF2vec; BERT; DBpedia; node2vec; Tensor2Tensor; t-SNE; HermiT; Scikit Cited in: 3 Documents all top 5 Cited by 13 Authors 1 Antonyrajah, Denvar 1 Bienvenu, Meghyn 1 Chen, Jiaoyan 1 Cheng, Hong 1 Holter, Ole Magnus 1 Horrocks, Ian 1 Hu, Pan 1 Jiménez-Ruiz, Ernesto 1 Ortiz, Magdalena 1 Yu, Jeffrey Xu 1 Zhao, Kangfei 1 Zheng, Weiguo 1 Zou, Lei Cited in 2 Serials 1 Information Sciences 1 Machine Learning Cited in 1 Field 3 Computer science (68-XX) Citations by Year