Τίτλος:
Full-text support for publish/subscribe ontology systems
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
In this work, we envision a publish/subscribe ontology system that is able to index large numbers of expressive continuous queries and filter them against RDF data that arrive in a streaming fashion. To this end, we propose a SPARQL extension that supports the creation of full-text continuous queries and propose a family of main-memory query indexing algorithms which perform matching at low complexity and minimal filtering time. We experimentally compare our approach against a state-of-the-art competitor (extended to handle indexing of full-text queries) both on structural and full-text tasks using real-world data. Our approach proves two orders of magnitude faster than the competitor in all types of filtering tasks. © Springer International Publishing Switzerland 2016.
Συγγραφείς:
Zervakis, L.
Tryfonopoulos, C.
Skiadopoulos, S.
Koubarakis, M.
Περιοδικό:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Λέξεις-κλειδιά:
Indexing (of information), And filters; Continuous queries; Main memory; Ontology system; Orders of magnitude; Publish/subscribe; Query indexing; State of the art, Semantic Web
DOI:
10.1007/978-3-319-34129-3_15
