Proactive and reactive context reasoning architecture for smart web services. (3rd March 2020)

• Record Type: Journal Article
• Authors: Sekkal, Nawel; Benslimane, Sidi Mohamed; Mrissa, Michael; Park, Cheol Young; Boudaa, Boudjemaa
• Is Part Of: International journal of data mining, modelling and management. Volume 12:Number 1(2020)
• Page Start: 1
• Page End: 27
• Publication Date: 2020-03-03
• Subjects: smart web service -- the web of things -- context reasoning -- proactive -- reactive -- multi-entity Bayesian networks -- MEBNs -- PR-OWL; Data mining -- Periodicals; Information science -- Periodicals; Databases -- Periodicals; 005.7
• Languages: English
• ISSNs: 1759-1163

Abstract

The web of things (WoT) uses web technologies to connect embedded objects to each other and to deliver services to stakeholders. The context of these interactions (situation) is a key source of information which can be sometimes uncertain. In this paper, we focus on the development of intelligent web services. The main requirements for intelligent service are to deal with context diversity, semantic context representation and the capacity to reason with uncertain information. From this perspective, we propose a framework for intelligent services to deal with various contexts, to reactively respond to real-time situations and proactively predict future situations. For the semantic representation of context, we use PR-OWL, a probabilistic ontology based on multi-entity Bayesian networks. PR-OWL is flexible enough to represent complex and uncertain contexts. We validate our framework with an intelligent plant watering use case to show its reasoning capabilities.