The window validity problem in rule-based stream reasoning

Conference item

Rule-based temporal query languages provide the expressive power and flexibility required to capture in a natural way complex analysis tasks over streaming data. Stream processing applications, however, typically require near real-time response using limited resources. In particular, it becomes essential that the underpinning query language has favourable computational properties and that stream processing algorithms are able to keep only a small number of previously received facts in memory at any point in time without sacrificing correctness. In this paper, we propose a recursive fragment of temporal Datalog with tractable data complexity and study the properties of a generic stream reasoning algorithm for this fragment. We focus on the window validity problem as a way to minimise the number of time points for which the stream reasoning algorithm needs to keep data in memory at any point in time.

Authors: Ronca, A; Kaminski, M; Cuenca Grau, B; Horrocks, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: AAAI Press
• Host title: Proceedings of the Sixteenth International Conference on Principles of Knowledge Representation and Reasoning (KR 2018)
• Pages: 571-580
• Publication date: 2018-09-24
• Acceptance date: 2018-08-10
• Event title: KR 2018: 16th International Conference on Principles of Knowledge Representation and Reasoning
• Event location: Tempe, AZ, USA
• Event website: http://reasoning.eas.asu.edu/kr2018
• Event start date: 2018-10-29
• Event end date: 2018-11-02
• ISBN: 9781577358039
• Language: English
• Keywords: window; Datalog; query answering; stream reasoning; query containment; rule-based; stream processing; temporal reasoning