An Approach of Trajectory Clustering Using Distributed Representation of User Movement
- Resource Type
- Conference
- Authors
- Hirota, Masaharu; Oda, Tetsuya
- Source
- 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech) Life Sciences and Technologies (LifeTech), 2021 IEEE 3rd Global Conference on. :75-76 Mar, 2021
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Social networking (online)
Conferences
Urban planning
Life sciences
Trajectory
Word2vec
Skip-gram
movement analysis
mobility patterns
- Language
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.