The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Semantic Framework for Touristic Information Systems
Abstract
The Web is a crucial means for the dissemination of touristic information. However, most touristic information resources are stored directly in Web pages or in relational databases that are accessible through ad-hoc Web applications, and the use of automated processes to search, extract and interpret information can hardly be implemented. The Semantic Web technologies, aiming at representing the background knowledge about Web resources in a computational way, can be an important contribution to the development of such automated processes. This chapter introduces the concept of touristic object, giving special attention to the representation of temporal, spatial, and thematic knowledge. It also proposes a three-layered architecture for the representation of touristic objects in the Web. The central part is the domain layer, defining a Semantic Model for Tourism (SeMoT) to describe concepts, relationships, and constraints using ontologies. The data layer supports the mapping of touristic information in relational databases into Resource Description Framework (RDF) virtual graphs following the SeMoT specification. The application layer deals with the integration of information from different data sources into a unified knowledge model, offering a common vocabulary to describe touristic information resources. Finally, we also show how to use this framework for planning touristic itineraries.
Related Content
|
Suneel Kumar, Varinder Kumar, Marco Valeri, Nisha Devi, Kamlesh Attri.
© 2024.
28 pages.
|
|
Tuğçe Şimşek.
© 2024.
28 pages.
|
|
Maja Turnsek, Adele Ladkin.
© 2024.
25 pages.
|
|
Alkistis Papaioannou, Panagiotis Dimitropoulos.
© 2024.
17 pages.
|
|
Kannapat Kankaew, Parinya Nakpathom, Alhuda Chanitphattana, Hataipat Phungpumkaew, Kwanporn Boonnag, Gilbert C. Magulod Jr.
© 2024.
16 pages.
|
|
Jessica Patrícia Ferreira, Bruno Barbosa Sousa, Nuno Costa.
© 2024.
26 pages.
|
|
Anup Kaith, Geeta Sachdeva.
© 2024.
22 pages.
|
|
|