FedX: Optimization Techniques for Federated Query Processing on Linked Data
By Andreas Schwarte, Peter Haase, Katja Hose, Ralf Schenkel, Michael Schmidt. International Workshop on the Semantic Web, 2011
390 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing
View Paper: https://www.semanticscholar.org/paper/642843a5541b338f4a067777386eeb4839adcaa4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sarasi Lalithsena
- Olaf Hartig
- Ruben Verborgh
- Pieter Colpaert
- Miel Vander Sande
- Laurens De Vocht
- Gerald Haesendonck
- Ben De Meester
In Computer Networks and Communications
- Sarasi Lalithsena
- Olaf Hartig
- Ruben Verborgh
- Pieter Colpaert
- Miel Vander Sande
- Laurens De Vocht
- Gerald Haesendonck
- Ben De Meester
In Signal Processing
Citations in the corpus
- Domain-specific Knowledge Extraction from the Web of Data (2018, methodology): “In [Schwarte et al. 2011] [Hartig et al. 2009] [de Oliveira et al. 2012] [Tran et al. 2010], authors have proposed different techniques for dataset identification for query answering.”
- Triple Pattern Fragments: A low-cost knowledge graph interface for the Web (2016, methodology): “[66], who tested the following SPARQL endpoint federation systems: ANAPSID [53], ANAPSID EG (ANAPSID using Exclusive Groups), FedX [67] (with a warmed-up cache), and SPLENDID [68].”