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Article

LARS: A logic-based framework for analyzing reasoning over streams

Authors:

Michael FinkAuthors Info & Claims

AAAI'15: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence

Pages 1431 - 1438

Published: 25 January 2015 Publication History

Abstract

The recent rise of smart applications has drawn interest to logical reasoning over data streams. Different query languages and stream processing/reasoning engines were proposed. However, due to a lack of theoretical foundations, the expressivity and semantics of these diverse approaches were only informally discussed. Towards clear specifications and means for analytic study, a formal framework is needed to characterize their semantics in precise terms. We present LARS, a Logic-based framework for Analyzing Reasoning over Streams, i.e., a rule-based formalism with a novel window operator providing a flexible mechanism to represent views on streaming data. We establish complexity results for central reasoning tasks and show how the prominent Continuous Query Language (CQL) can be captured. Moreover, the relation between LARS and ETALIS, a system for complex event processing is discussed. We thus demonstrate the capability of LARS to serve as the desired formal foundation for expressing and analyzing different semantic approaches to stream processing/reasoning and engines.

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Cited By

de Leng DBonte P(2024)Last Night in Sweden: A Vision for Resource-Intelligent Stream ReasoningProceedings of the 18th ACM International Conference on Distributed and Event-based Systems10.1145/3629104.3666035(103-109)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3629104.3666035
Tommasini RCalvaresi DCalbimonte JElkind EVeloso MAgmon NTaylor M(2019)Stream Reasoning AgentsProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331894(1664-1680)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331894
Brandt SKalayci ERyzhikov VXiao GZakharyaschev M(2019)Querying log data with metric temporal logicJournal of Artificial Intelligence Research10.1613/jair.1.1122962:1(829-877)Online publication date: 17-Apr-2019
https://dl.acm.org/doi/10.1613/jair.1.11229
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cover image Guide Proceedings

AAAI'15: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence

January 2015

4331 pages

ISBN:0262511290

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Association for the Advancement of Artificial Intelligence

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AAAI Press

Publication History

Published: 25 January 2015

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Cited By

de Leng DBonte P(2024)Last Night in Sweden: A Vision for Resource-Intelligent Stream ReasoningProceedings of the 18th ACM International Conference on Distributed and Event-based Systems10.1145/3629104.3666035(103-109)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3629104.3666035
Tommasini RCalvaresi DCalbimonte JElkind EVeloso MAgmon NTaylor M(2019)Stream Reasoning AgentsProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331894(1664-1680)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331894
Brandt SKalayci ERyzhikov VXiao GZakharyaschev M(2019)Querying log data with metric temporal logicJournal of Artificial Intelligence Research10.1613/jair.1.1122962:1(829-877)Online publication date: 17-Apr-2019
https://dl.acm.org/doi/10.1613/jair.1.11229
Hirzel MBaudart GBonifati ADella Valle ESakr SAkrivi Vlachou A(2018)Stream Processing Languages in the Big Data EraACM SIGMOD Record10.1145/3299887.329989247:2(29-40)Online publication date: 11-Dec-2018
https://dl.acm.org/doi/10.1145/3299887.3299892
Diwold KMayer SEinfalt AParreira JHodges JAnicic DMosshammer RJanowicz KKuhn WCena FHaller AVamvoudakis K(2018)Grid watch dogProceedings of the 8th International Conference on the Internet of Things10.1145/3277593.3277601(1-8)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3277593.3277601
Das AGandhi SZaniolo CCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)ASTROProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3269223(1863-1866)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3269223
Dao-Tran MEiter T(2017)Streaming multi-context systemsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171642.3171785(1000-1007)Online publication date: 19-Aug-2017
https://dl.acm.org/doi/10.5555/3171642.3171785
Beck HDao-Tran MEiter T(2016)Equivalent stream reasoning programsProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060750(929-935)Online publication date: 9-Jul-2016
https://dl.acm.org/doi/10.5555/3060621.3060750
Della Valle EDell'Aglio DMargara AGal AWeidlich MKalogeraki VVenkasubramanian N(2016)Taming velocity and variety simultaneously in big data with stream reasoningProceedings of the 10th ACM International Conference on Distributed and Event-based Systems10.1145/2933267.2933539(394-401)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1145/2933267.2933539
Su XGilman EWetz PRiekki JZuo YLeppänen T(2016)Stream Reasoning for the Internet of ThingsProceedings of the 6th International Conference on Web Intelligence, Mining and Semantics10.1145/2912845.2912853(1-10)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1145/2912845.2912853
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