Abstract : We address the problem of predicting SPARQL query performance. We use machine learning techniques to learn SPARQL query performance from previously executed queries. We show how to model SPARQL queries as feature vectors, and use k -nearest neighbors regression and Support Vector Machine with the nu-SVR kernel to accurately (R^2 value of 0.98526) predict SPARQL query execution time.
Type de document :
Poster
11th Extended Semantic Web Conference (ESWC2014), May 2014, Crete, Greece. pp.222 - 225, 2014, <10.1007/978-3-319-11955-7_23>
https://hal.inria.fr/hal-01075489
Contributeur : Rakebul Hasan <>
Soumis le : jeudi 23 octobre 2014 - 13:25:08
Dernière modification le : mercredi 29 juillet 2015 - 01:19:44
Document(s) archivé(s) le : samedi 24 janvier 2015 - 10:06:04
