A Decision Support System for Inexperienced Volunteer Guides to Assist Increased Inbound Tourists in Japan

In recent years, Japan is experiencing a drastic increase of inbound tourists. In order to improve the environment for accepting foreign tourists visiting Japan, the Licensed Guide Interpreters Act was partially revised in 2018, which allows anyone to work as a compensated guide interpreter without...

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Vydáno v:Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics s. 486 - 492
Hlavní autoři: Okazaki, Masahiro, Ohira, Yuki, Fukuyama, Kei, Kuwano, Masashi, Ishii, Akira
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 11.10.2020
Témata:
collaborative filtering
Data mining
decision support system
Decision support systems
Filtering
guide interpreter
inbound tourist
Licenses
Organizations
Planning
Urban areas
ISSN:2577-1655
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Shrnutí:In recent years, Japan is experiencing a drastic increase of inbound tourists. In order to improve the environment for accepting foreign tourists visiting Japan, the Licensed Guide Interpreters Act was partially revised in 2018, which allows anyone to work as a compensated guide interpreter without the national license. Because inbound tourists have a wide variety of preferences on sightseeing, guides are needed to manage those diversified or sometimes complex requests flexibly. Thus, it is an important issue to ensure a quality of the interpreted guide services, as such uncertified guides may include inexperienced volunteers. This paper proposes a decision support system for inexperienced guides who is developing sightseeing plans for foreign visitors. First, inbound tourist behavior patterns in a city in Japan are extracted from a guide log data, which are recorded by some volunteer guides. By applying the collaborative filtering, the support system is constructed that predict and recommend sightseeing spots and activities by inputting new visitors' interested spots and/or activities. Experimental test demonstrates that the proposed system holds a certain level of accuracy.
ISSN:2577-1655
DOI:10.1109/SMC42975.2020.9283039