Salma Najar

Semantic representation of context models: a framework for analyzing and understanding

Context-aware systems are applications that adapt themselves to several situations involving user, network, data, hardware and the application itself. In this paper, we review several context models proposed in different domains: content adaptation, service adaptation, information retrieval, etc. The purpose of this review is to expose the representation of this notion semantically. According to this, we propose a framework that analyzes and compares different context models. Such a framework intends helping understanding and analyzing of such models, and consequently the definition of new ones. This framework is based on the fact that context-aware systems use context models in order to formalize and limit the notion of context and that relevant information differs from a domain to another and depends on the effective use of this information. Based on this framework, we consider in this paper a particular application domain, Business Processes, in which the notion of context remains unexplored, although it is required for flexibility and adaptability. We propose, in this paper, an ontology-based context model focusing on this particular domain.

Service Discovery Mechanism for an Intentional Pervasive Information System

Pervasive Information System (PIS) provides a new vision of Information System available anytime and anywhere. The users of these systems must evolve in a space of services, in which several services are offered to him. However, PIS should enhance the transparency and efficiency of the system. We believe that a user-centric vision is needed to ensure a transparent access to the frequently changing space of services regardless of how to perform it. In this paper, we propose a new approach of PIS, both context-aware and intentional called IPIS. In this approach, services are proposed in order to satisfy users intention in a given context. Then, we propose a context-aware intentional service discovery mechanism. Such mechanism is based on an extension of OWL-S taking into account the notion of context and intention. We present in this paper IPIS platform. Then, we detail the proposed service discovery mechanism and present experimental results that demonstrate the advantage of using our proposition.

Service discovery and prediction on Pervasive Information System

Recent evolution of technology and its usages, such as Bring Your Own Device and Internet of Things, transformed the way we interact with Information Systems , leading to a new generation of IS, called the Pervasive Information Systems. These systems have to face heterogeneous pervasive environments and hide the complexity of such environment end-user. In order to reach transparency and proactivity necessary for successful PIS, new discovery and prediction mechanisms are necessary. In this paper, we present a new user-centric approach for PIS and propose new service discovery and prediction based on both user’s context and intentions. Intentions allow focusing on goals user wants to satisfy when requesting a service. Those intentions rise in a given context, which influence the service implementation. We propose a service discovery mechanism that observes user’s context and intention in order to offer him/her the most appropriate service satisfying her/his intention on the current context. We also propose a prediction mechanism that tries to anticipate user’s intentions considering the user’s history and the observed context. We evaluate both mechanisms and discuss advanced features future PIS will have to deal with.

Towards semantic modeling of intentional pervasive information systems

A Pervasive Information System (PIS) provides a new vision of Information System (IS) that intends to make them available anytime and anywhere. PIS evolve in a space of services including physical ones embedded on the physical world, and logical ones representing traditional IS. However, this system should be modeled in such a way that enhances the transparency and efficiency of the system. Thus, we believe that a user-centric vision taking into account users intention is needed to ensure an evolution with transparency in a frequently changing space. The objective of this paper is to propose a semantic modeling of an intentional PIS based on a semantic service description that considers both intention corresponding to the service and context in which it is supposed to be valid and executed.

A New Approach for Service Discovery and Prediction on Pervasive Information System

Abstract Recent evolution of technology transformed the way we interact with Information Systems (IS), leading to a new generation of IS, the Pervasive Information Systems (PIS). These systems have to face heterogeneous pervasive environments, whose complexity they must hide from end-user. In order to reach transparency and proactivity necessary for successful PIS, new discovery and prediction mechanisms are necessary. In this paper, we propose a new user-centric approach for service discovery and prediction on PIS based on both users context and intentions. Intentions allow focusing on goals user wants to satisfy when requesting a service. Those intentions rise in a given context, which may condition the service implementation. We propose then a service discovery mechanism that observes users context and intention in order to offer him the service that may best satisfy her/his intention on the current context. We also propose a prediction mechanism that tries to anticipate users intentions considering the observed context and users history.