The Design and Development of Alternative Tourism Ontology in the COVID-19 Situation
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Abstract
Currently, countries around the world are facing Coronavirus disease 2019 (COVID-19), making it necessary to shut down the countries to prevent infection. As a result, both Thai and foreign tourists cannot travel across Thailand. In addition, domestic tourists are unable to travel to different regions. This research aims to design and develop an alternative tourism ontology in the COVID-19 scenario. This ontology is applied to search for tourist attractions in Thailand that are comparable to international destinations, or domestic tourist attractions in a region that look like those of another region. To search for the information, this research uses the keyword format collected from 400 tourists. The ontological retrieval efficiency was assessed by comparing six similarity measurement techniques which are 1) 2-Level Euclidean Distance (2L-ED), 2) 5- Level Euclidean Distance (5L-ED), 3) 2-Level Jaccard Similarity (2L-JS), 4) 5-Level Jaccard Similarity (5L-JS), 5) 2-Level Cosine Similarity (2L-CS), and 6) 5-Level Cosine Similarity (5L-CS). The most suitable methods used to search for tourist attractions in Thailand that might replace foreign tourist attractions are the 2-Level Jaccard Similarity (2L-JS) and the 2-Level Cosine Similarity (2L-CS). The developed tourism ontology is achieved with an F-measure score of 97.43 per cent.
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