Authors
Mohamed Sherif, Kevin Dreßler, Panayiotis Smeros, Axel-Cyrille Ngonga Ngomo
Publication date
2017/2/10
Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Volume
31
Issue
1
Description
Geospatial data is at the core of the Semantic Web, of which the largest knowledge base contains more than 30 billions facts. Reasoning on these large amounts of geospatial data requires efficient methods for the computation of links between the resources contained in these knowledge bases. In this paper, we present Radon–efficient solution for the discovery of topological relations between geospatial resources according to the DE9-IM standard. Our evaluation shows that we outperform the state of the art significantly and by several orders of magnitude.
Total citations
2017201820192020202120222023202461871013572
Scholar articles
M Sherif, K Dreßler, P Smeros, ACN Ngomo - Proceedings of the AAAI Conference on Artificial …, 2017
MA Sherif, K Dreßler, P Smeros, ACN Ngomo - arXiv preprint arXiv:1611.06128, 2016