Understanding tourists’ urban images with geotagged photos using convolutional neural networks
- 주제(키워드) Image data mining Geotagged photos Flickr Convolutional neural network Inception v3 model , Image data mining Geotagged photos Flickr Convolutional neural network Inception v3 model
- 주제(기타) 사회과학
- 주제(기타) 지리학
- 주제(기타) 지리학일반
- 주제(기타) 지리정보시스템
- 설명문(URI) https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002583717
- 등재 KCI등재
- 발행기관 한국공간정보학회
- 발행년도 2020
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000169695
- 본문언어 영어
- Published As https://dx.doi.org/10.1007/s41324-019-00285-x
초록/요약
This study aims to track down representative images and elements of sightseeing attractions by analyzing the photos uploaded on Flickr by Seoul tourists with the image mining technique. For this purpose, we crawled the photos uploaded on Flickr and classified users into residents and tourists; drew 11 region of attractions (RoA) in Seoul by analyzing the spatial density of the photos; classified the photos into 1000 categories and then 14 categories by grouping 1000 categories by utilizing Inception V3 model; analyzed the characteristics of the photo image by RoA. Key findings of this study are that tourists are interested in old palaces, historical monuments, stores, food, etc. and those key elements are distinguished from the major sightseeing attractions in Seoul. More specifi- cally, tourists are more interested in palaces and cultural assets in Jongno and Namsan, food and restaurants in Shinchon, Hongdae, Itaewon, Yeouido, Garosu-gil, and Apgujeong, war monuments or specific artifacts in War Memorial and the National Museum of Korea, facilities, temples, and pictures of cultural properties in Samsung Station, and toyshops in Jamsil. This study is meaningful in three folds: first, it tries to analyze urban image through the photos posted on SNS by tourists. Second, it uses deep learning technique to analyze the photos. Third, it classifies and analyzes the whole photos posted by Seoul tourists while most of other researches focus on only specific objects. However, this st
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