Context-Aware and Linked Open Data Based Service Discovery

摘要

Context-aware Service Discovery process is the task of identifying relevant services that could satisfy user needs while considering contextual information. Depending on such context information, the discovery process may become a challenging task as it requires to consider different kinds of constraints. In tourism domain, for example, context-aware service discovery process has to take into account functional information (what functionalities does a service offer) and non-functional information (such as user profile and preferences or information about her/his surrounding environment). To deal with context-aware services discovery issue, researchers proposed solutions that rely on semantic Web technologies and particularly ontologies to describe and discover services. However, ontologies are generally not-interconnected and limited because they focus on specific domains. In this paper, we propose a novel discovery approach for context-aware services which relies on Linked Open Data (LOD) instead of ontologies. First, we propose a model to describe both functional and non-functional properties of context-aware services. Then, we enrich the service model instances with semantic data from LOD. Based on enriched descriptions, we propose matchmaking algorithms to satisfy a user's needs in a given context. We performed experiments on touristic services. Results show that using LOD for context-aware service discovery is promising regarding discovery effectiveness.