2021年
An Approach of Trajectory Clustering Using Distributed Representation of User Movement.
LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
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- 開始ページ
- 75
- 終了ページ
- 76
- 記述言語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/LifeTech52111.2021.9391965
- 出版者・発行元
- IEEE
Many tourists upload content about tourist attractions to social media sites. Understanding tourist mobility using the contents benefits numerous applications, such as tourism recommendation and city planning. In this study, we propose a method for trajectory clustering of user movement. Our approach uses an improved skip-gram model to learn movements between a pair of locations quantized by their latitude and longitude. The generated embedding vectors represent the relationships between the movements from one area to the next. We demonstrated that the embedded vectors generated using our proposed method could cluster users’ trajectories.
- リンク情報
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- DOI
- https://doi.org/10.1109/LifeTech52111.2021.9391965
- DBLP
- https://dblp.uni-trier.de/rec/conf/lifetech/HirotaO21
- URL
- https://dblp.uni-trier.de/conf/lifetech/2021
- URL
- https://dblp.uni-trier.de/db/conf/lifetech/lifetech2021.html#HirotaO21
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104593068&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85104593068&origin=inward
- ID情報
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- DOI : 10.1109/LifeTech52111.2021.9391965
- ISBN : 9781665418751
- DBLP ID : conf/lifetech/HirotaO21
- SCOPUS ID : 85104593068