Name
Abstract | ||
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For avoiding excessive congestion of tourists that causes overtourism, we propose a Generic Point of Interest (POI), which is an alternative sightseeing spot potentially attractive enough for tourists to replace a well-known sightseeing spot. We also propose a method to discover generic POIs and evaluate it. While the rapid spread of social networking services (SNSs) and social media makes tourism more familiar to people, it is further aggravating overtoursim around the world due to the nature of SNSs and social media, where users simultaneously find the same posts or articles recommending specific tourist spots and are attracted to the same destinations at the same time. As overtourism has severe influences on both visitors and local residents, it is essential to solve this problem. Although there are many studies providing ways of recommending less crowded tourist spots or mining less-known spots in a famous sightseeing area, we cannot apply those methods as a fundamental solution for overtourism for two reasons: 1) in many cases, the number of tourists already exceeds the touring area's total capacity; and 2) many approaches relying on a number of user-generated data points cannot discover unbusy sightseeing spots since users hardly post reviews nor images. To address these challenges, we propose a novel concept of generic POIs, alternative sightseeing spots to famous spots, and we propose a method to discover generic POIs, whose images are similar to those of existing famous sightseeing spots. We also evaluate our method with collected examples of generic POIs. We hope that the proposed method will help alleviate the overtourism problem in the real world as a first step.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3410530.3414421 | UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers
Virtual Event
Mexico
September, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-8076-8 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hisao Katsumi | 1 | 1 | 0.35 |
| Wataru Yamada | 2 | 29 | 15.22 |
| Keiichi Ochiai | 3 | 7 | 3.21 |