Ontology-driven car pooling via semantic matchmaking: a context-aware approach
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چکیده
Despite remarkable progress, location-based discovery of transportation services is currently hindered by the superficial information content associated to resources. Dynamic entities like vehicles in car pooling and fleet management scenarios are characterized only by basic properties such as geographical coordinates, name and a general category. This allows to support only exact matches, often leading to poor user satisfaction. The paper proposes a framework based on knowledge representation languages and Semantic Web technologies to annotate OpenStreetMap resources with articulate information endowed with formal meaning, so supporting semantic-based matchmaking to filter and rank resources according to relevance. The approach was assessed in a case study on an Intelligent Transport System (ITS) enabling advanced discovery, scheduling and tracking of car pooling services.
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