Abstract
AbstractWe introduce a novel logic-based system for reasoning over data streams, which relies on a framework enabling a tight, fine-tuned interaction between Apache Flink and the
$${{\mathcal I}^2}$$
-DLV system. The architecture allows to take advantage from both the powerful distributed stream processing capabilities of Flink and the incremental reasoning capabilities of
$${{\mathcal I}^2}$$
-DLV, based on overgrounding techniques. Besides the system architecture, we illustrate the supported input language and its modeling capabilities, and discuss the results of an experimental activity aimed at assessing the viability of the approach.
Publisher
Cambridge University Press (CUP)
Subject
Artificial Intelligence,Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software
Reference26 articles.
1. Apache flink: Stream and batch processing in a single engine;Carbone;IEEE Data Engineering Bulletin 38,2015
2. Stream reasoning: A survey and outlook
3. Beck, H. , Bierbaumer, B. , Dao-Tran, M. , Eiter, T. , Hellwagner, H. and Schekotihin, K. 2017. Stream reasoning-based control of caching strategies in CCN routers. In IEEE International Conference on Communications, ICC 2017, Paris, France, May 21–25, 2017. IEEE, 1–6.
4. C-SPARQL: A CONTINUOUS QUERY LANGUAGE FOR RDF DATA STREAMS
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献