Reaction RuleML 1.0: Standardized Semantic Reaction Rules

Paschke, Adrian; Boley, Harold; Zhao, Zhili; Teymourian, Kia; Athan, Tara

doi:10.1007/978-3-642-32689-9_9

Cited by 25 publications

(19 citation statements)

References 13 publications

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“…Increasing amount of literature emerges on reactivity related to the Web (Paschke, 2014), (Hausmann and Bry, 2013), (Paschke et al, 2012). The rationale behind these studies is an event-based system, which in turn rely on ECA Rules.…”

Section: Event-condition-action (Eca) Paradigmsupporting

confidence: 44%

Facilitating the Reactive Web - A Condition Action System using Node.js

Groflin

Bosch²,

Guggisberg

et al. 2015

Proceedings of the 11th International Conference on Web Information Systems and Technologies

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Abstract:The orchestration of the Web is a big issue for Web users all around the world. Web users have a high interest in services, which are able to personalise and customise the Web. However, for Web reactivity there exists only a few limited solutions that allow the aggregation of Web resources. This paper takes a look at existing eventbased methods that build upon Event-Condition-Action (ECA) Rules and Complex Event Processing (CEP). Moreover, this paper illustrates the architecture of a fully functioning Condition Action System prototype for the creation of reactivity in between Web resources. In a proof of concept, we could detect and determine the change interval of electronic newspaper headlines. With the proposed system, we are able to orchestrate Web resources e.g. Detecting Web Changes.

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Section: Event-condition-action (Eca) Paradigmsupporting

confidence: 44%

Facilitating the Reactive Web - A Condition Action System using Node.js

Groflin

Bosch²,

Guggisberg

et al. 2015

Proceedings of the 11th International Conference on Web Information Systems and Technologies

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“…[17] Reaction RuleML 1.0 incorporates this reactive spectrum of rules into RuleML 1.0 employing a system of step-wise extensions of the Deliberation RuleML 1.0 foundation starting with an extension of Derivation Rules (DR) for spatio-temporal-interval reasoning. [2,20] …”

Section: Reaction Ruleml For Reaction Rulessupporting

confidence: 42%

“…[16,2,20] For common elements which occur in most typical rule languages, Reaction RuleML introduces generic XML elements. These generic XML elements can be given a specific sort using the typing mechanism (@type) of RuleML.…”

Section: Metamodel and External Type Systemsmentioning

confidence: 43%

Reaction RuleML 1.0 for Rules, Events and Actions in Semantic Complex Event Processing

Paschke

2014

Rules on the Web. From Theory to Applications

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Abstract. Reaction RuleML is a standardized rule markup language for the representation and interchange of reaction rules. This paper gives an introduction to the core knowledge representation mechanisms of Reaction RuleML 1.0 such as multi-sorted signatures and their interpretation, action primitives for knowledge updates, interchange and testing, ordersorted external type systems and the Reaction RuleML metamodel, scopes and mode declarations, semantic profiles, imports of documents, modules and messages. These mechanisms form the basis for an adequate treatment of rules, events and actions, as needed in Semantic Complex Event Processing (SCEP), such as, interchange, translation and testing based on the intended semantics defined in semantic profiles; modularization and distribution of knowledge interfaces with their signatures defining, e.g., complex event detection patterns; closed scoped reasoning on top of scoped modules with dynamic constructive views on meta knowledge; transactional complex actions; conversation based message interchange for Question Answering (Q&A) and rule-based agent architectures such as RuleResponder, etc.

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“…In terms of expressive power, KELPS is similar to Reaction RuleML [16], and much of the comparison with other systems presented in [16] also holds for KELPS. Moreover, our earlier papers [11,12,13,14] also include extensive discussions of the relationships between LPS and production systems, BDI agents, event-condition action rules in active databases, action languages in AI and other models of computation.…”

Section: Related Workmentioning

confidence: 42%

“…They are implicit in Statecharts [5] and BDI agents plans. They are the core of Reaction RuleML [16].…”

Section: Introductionmentioning

confidence: 45%

A Logical Characterization of a Reactive System Language

Kowalski

Sadri

2014

Rules on the Web. From Theory to Applications

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Abstract. Typical reactive system languages are programmed by means of rules of the form if antecedent then consequent. However, despite their seemingly logical character, hardly any reactive system languages give such rules a logical interpretation. In this paper, we investigate a simplified reactive system language KELPS, in which rules are universally quantified material implications, and computation attempts to generate a model that makes the rules true.The operational semantics of KELPS is similar to that of other reactive system languages, and is similarly incomplete. It cannot make a rule true by making its antecedent false, or by making its consequent true whether or not its antecedent becomes true. In this paper, we characterize the reactive models computed by the operational semantics. Informally speaking, a model is reactive if every action in the model is an instance of an action in the consequent of a rule whose earlier conditions are true.

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Reaction RuleML 1.0: Standardized Semantic Reaction Rules

Cited by 25 publications

References 13 publications

Facilitating the Reactive Web - A Condition Action System using Node.js

Facilitating the Reactive Web - A Condition Action System using Node.js

Reaction RuleML 1.0 for Rules, Events and Actions in Semantic Complex Event Processing

A Logical Characterization of a Reactive System Language

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