WRAST: Warehousing Relatedness-Aware Semantic Trajectories

This work introduces methodologies for extending the modelling and querying capabilities of Trajectories Data Warehouses (TDW) in the context of semantic trajectories. Specifically, we incorporate the notion of Semantic Relatedness (SR) as part of the formal model of a TDW, which enables capturing the similarity between different annotations describing Points of Interest (POI), locations and activities used in specifying semantic trajectories. We formally define the functionality capturing the relatedness between different terms used as descriptors in semantic trajectories and present the Semantic Relatedness in Trajectories Data Warehouse (SR-TDW) model. We also present the newly enabled (categories of) queries in the SR-TDWmodel and illustrate them with specific examples. Our experimental observations demonstrate the benefits of the proposed approaches in terms of enriched answer-sets of the common OLAP-based queries and illustrate the sensitivity in terms of the relatedness measure.