Data-driven Modelization and Knowledge Graph Generation within the Tourism Domain

Tracking #: 3155-4369

This paper is currently under review
Authors: 
Diego Reforgiato Recupero
Luca Secchi
Alessandro Chessa
Gianni Fenu
Francesco Osborne
Angelo Salatino
Enrico Motta

Responsible editor: 
Katja Hose

Submission type: 
Full Paper
Abstract: 
The tourism and hospitality sectors have become increasingly important in the last few years and the companies operating in this field are constantly challenged in providing new innovative services. At the same time (big) data has become the “new oil” of this century and Knowledge Graphs are emerging as the most natural way to collect, refine, and structure this heterogeneous information. In this paper, we present a methodology for semi-automatic generating a Tourism Knowledge Graph (TKG), which can be used for supporting a variety of intelligent services in this space, and a novel ontology for modelling this domain, the Tourism Analytics Ontology (TAO). Our approach processes and integrates data from Booking.com, AirBnB, DBpedia and GeoNames. Due to its modular structure, it can be easily extended to include new data sources or to apply new enrichment and refinement functions. We report a comprehensive evaluation of the functional, logical, and structural dimensions of TKG and TAO.
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