Pervasive Learning System Based on a Scenario Model Integrating Web Service Retrieval and Orchestration

Cuong Ngyuen Pham, Serge Garlatti, Simon Lau, Benjamin Barbry, Thomas Vantroys

Abstract


We are interested in learning and working scenarios integrating web service retrieval and orchestration in pervasive TEL systems in a learning situation at workplace. This paper proposes a context-aware model of corporate learning and working scenarios in e-retail environment such as shops and hypermarkets. This scenario model enables us to select how to achieve activities according to the current situation. We outline the semantic description of web services to enable the selection, composition and execution of web services to achieve objectives specified by learning and working activities. We propose a context-aware and adaptive model for pervasive learning systems. This model enables the selection of the relevant methods or services to realize activities according to the current situation. Moreover, we also build and develop an Intelligent Selling Space (ISS) architecture that serves as an infrastructure for service management and execution in e-retail environment.

Keywords


Adaptation, Context-aware, Hierarchical task model, Learning and working situation, Pervasive learning, Service description, Service requirement, Task/method paradigm.

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International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
Creative Commons License
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