Characterizing Generic POI: A Novel Approach for Discovering Tourist Attractions

Abstract

With the rapid spread of social networking services (SNS) and social media, tourism has become a more accessible leisure activity. While many tourists visit well-known tourist destinations, the number of tourists visiting lesser-known ones in non-urban or rural areas has been in decline, and the decline has been exacerbating various problems such as economic disparities. Under these circumstances, it is becoming increasingly important to attract tourists to lesser-known areas with few tourism resources, because attracting tourists brings various positive effects to local residents and municipalities. Existing efforts to attract tourists include studies on tourist spot mining, which search a tourist destination for sightseeing spots that are worth visiting but relatively less well known, based on user-generated content about spots on the Web, such as posts on SNS and images on photo-sharing services. However, as they rely on the amount of user-generated content about potential sightseeing spots to be mined, these methods are limited in discovering a new sightseeing spot that is not recognized as a tourist attraction in advance. To address these challenges, we are inspired by an interesting phenomenon: a previously little-known spot that looks similar to a famous place becomes a hot topic on social media, attracting many people and suddenly becoming a popular tourist attraction. In this paper, we call such a spot with a similar appearance to a well-known one, as generic point-of-interest (POI), and we provide a novel concept of discovering new sightseeing spots by computationally finding generic POIs; we give a new perspective of discovering a new tourist attraction by characterizing a commonplace spot that has a similar appearance to a well-known one as a new tourist attraction. We also propose a pipeline implemented for mining generic POIs, where we calculate the similarity between candidate spots of generic POIs and famous sightseeing spots. Furthermore, we evaluate the feasibility of our approach both through human evaluation and through a photo contest on the Web we held with Tourism Shikoku. The results prove that our proposed method can discover new tourist destinations. The primal advantage of our approach is that it gifts new tourism value to a spot with at least a single place photo similar to a famous sightseeing spot, and thus it discovers a new tourist attraction even in areas with a minimal number of user-submitted images. We hope that our novel concept will be the first step in efforts to attract tourists in various regions around the world, enabling utilization of local spots that even the locals may not be aware of.