Detection of Suspicious Activity Using Different Rule Engines — Comparison of BaseVISor, Jena and Jess Rule Engines

Moskal, Jakub; Matheus, Christopher J.

doi:10.1007/978-3-540-88808-6_10

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…While PARTE utilizes the constraints of the domain to achieve these properties, it remains applicable to the broader domains of Time Series Analysis and Complex Event Processing because they have very similar properties with respect to event streams and performance requirements. This includes applications such as algorithmic stock trading [25][26][27] and monitoring network security [28,29]. PARTE's key design choices are a tiered architecture, the use of lock-free queues, and an actor execution model to provide upper bound guarantees on the event matching in a Rete network.…”

Section: Discussionmentioning

confidence: 99%

Parallel gesture recognition with soft real-time guarantees

Marr

Renaux

Hoste

et al. 2015

Science of Computer Programming

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Section: Discussionmentioning

confidence: 99%

Parallel gesture recognition with soft real-time guarantees

Marr

Renaux

Hoste

et al. 2015

Science of Computer Programming

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“…This reasoner supports rule-based inference over RDF graphs, and provides forward chaining realized by means of an internal RETE-based forward chaining interpreter [4]. The main advantage of using the JENA interpreter with respect to other Java compatible production rules interpreters, like for instance the Jess engine inspired by the open-source CLIPS project, is its direct compatibility with RDF data [16].…”

Section: Implementation Of a Prototypementioning

confidence: 99%

Using Semantic Web technologies and production rules for reasoning on obligations, permissions, and prohibitions1

Fornara

Colombetti

2019

AIC

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Nowadays the studies on the formalization, enforcement, and monitoring of policies and norms is crucial in different fields of research and in numerous applications. ODRL 2.2 (Open Digital Right Language) is a W3C standard policy expression language formalized using semantic web technologies. It is used to represent permitted and prohibited actions over a certain asset, and obligations required to be met by parties involved in the exchange of a digital asset. In this paper, we propose to extend the model of permission and obligation proposed by ODRL 2.2 in two directions. Firstly, by inserting in the model the notion of activation event or action and by expressing event and action as complex constructs having types and application-independent properties. Secondly, by considering the temporal aspects of obligations and permissions (expiration dates and deadlines) as part of their application independent model. The operational semantics of the proposed model of obligations and permissions is specified using Discrete State Machines and is computed using a production rule system. The proposed approach has been tested by developing a framework in Java able to get as input a set of policies formalized using Semantic Web languages, and to compute their evolution in time based on the events and actions that happen in the interaction among the parties involved in the policies.

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“…Moskal and Matheus provide a system automating vessel tracking information fusion [7] where three rule engines (BaseVISor, Jena and Jess) are compared qualitatively. Authors refer to their previous research and say that BaseVISor performs better than Jess on RDF-based problems.…”

Section: Related Workmentioning

confidence: 99%

Reasoning for Smart Space Application: Comparing Three Reasoning Engines CLIPS, Jess and Win-prolog

Gilman

Sánchez

Saloranta

et al. 2010

2010 10th IEEE International Conference on Computer and Information Technology

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This article presents Collect&Drop application, a pervasive system which utilizes RFID technology to store and pick digital content with mobile phones and play it with smart space's displays and speakers. Collect&Drop is implemented with the support of three reasoning engines, based on CLIPS, Jess and Win-Prolog. We discuss advantages and drawbacks of integrating a reasoning engine into the system, both qualitatively and quantitatively. Also comparison of the three engines implementations is made with respect to performance and resource consumption.

show abstract

Detection of Suspicious Activity Using Different Rule Engines — Comparison of BaseVISor, Jena and Jess Rule Engines

Cited by 8 publications

References 3 publications

Parallel gesture recognition with soft real-time guarantees

Parallel gesture recognition with soft real-time guarantees

Using Semantic Web technologies and production rules for reasoning on obligations, permissions, and prohibitions1

Reasoning for Smart Space Application: Comparing Three Reasoning Engines CLIPS, Jess and Win-prolog

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