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Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies
Sailing holiday activities represent a significant portion of the Blue Economy growth in Europe and across the world. Due to the global financial crisis, yacht ownership has declined, but demand for such holiday products remained steady, therefore shifting the yachters profile towards younger and le...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921707/ http://dx.doi.org/10.1007/s40558-022-00224-x |
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author | Komninos, Andreas Kostopoulos, Charalampos Garofalakis, John |
author_facet | Komninos, Andreas Kostopoulos, Charalampos Garofalakis, John |
author_sort | Komninos, Andreas |
collection | PubMed |
description | Sailing holiday activities represent a significant portion of the Blue Economy growth in Europe and across the world. Due to the global financial crisis, yacht ownership has declined, but demand for such holiday products remained steady, therefore shifting the yachters profile towards younger and less experienced consumers who prefer to charter boats, rather than own one. Boat chartering offers more flexibility to explore different regions from year to year, but this means that significantly more time must be spent planning the route, since local experience is absent. The tourists’ experience during the initial contemplation and planning phase, taking place weeks or months before an actual trip, and where a broad range of route options needs to be explored, could thus significantly benefit from support given by automated IT tools. Current literature demonstrates a complete lack of research in the development of itinerary recommendation systems in the context of sailing holidays. In this paper, we describe a methodology for the automatic generation of route recommendations, based on the semantic modelling of spatial data, and the determination of realistic sea route options, based on vessel density maps produced from raw AIS data. We demonstrate the implementation and results from this methodology using one of the most popular sailing regions of Greece, namely the Ionian Sea, as a case study. |
format | Online Article Text |
id | pubmed-8921707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-89217072022-03-15 Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies Komninos, Andreas Kostopoulos, Charalampos Garofalakis, John Inf Technol Tourism Original Research Sailing holiday activities represent a significant portion of the Blue Economy growth in Europe and across the world. Due to the global financial crisis, yacht ownership has declined, but demand for such holiday products remained steady, therefore shifting the yachters profile towards younger and less experienced consumers who prefer to charter boats, rather than own one. Boat chartering offers more flexibility to explore different regions from year to year, but this means that significantly more time must be spent planning the route, since local experience is absent. The tourists’ experience during the initial contemplation and planning phase, taking place weeks or months before an actual trip, and where a broad range of route options needs to be explored, could thus significantly benefit from support given by automated IT tools. Current literature demonstrates a complete lack of research in the development of itinerary recommendation systems in the context of sailing holidays. In this paper, we describe a methodology for the automatic generation of route recommendations, based on the semantic modelling of spatial data, and the determination of realistic sea route options, based on vessel density maps produced from raw AIS data. We demonstrate the implementation and results from this methodology using one of the most popular sailing regions of Greece, namely the Ionian Sea, as a case study. Springer Berlin Heidelberg 2022-03-15 2022 /pmc/articles/PMC8921707/ http://dx.doi.org/10.1007/s40558-022-00224-x Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Komninos, Andreas Kostopoulos, Charalampos Garofalakis, John Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title | Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title_full | Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title_fullStr | Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title_full_unstemmed | Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title_short | Automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
title_sort | automatic generation of sailing holiday itineraries using vessel density data and semantic technologies |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921707/ http://dx.doi.org/10.1007/s40558-022-00224-x |
work_keys_str_mv | AT komninosandreas automaticgenerationofsailingholidayitinerariesusingvesseldensitydataandsemantictechnologies AT kostopouloscharalampos automaticgenerationofsailingholidayitinerariesusingvesseldensitydataandsemantictechnologies AT garofalakisjohn automaticgenerationofsailingholidayitinerariesusingvesseldensitydataandsemantictechnologies |