Modeling User Trajectory Similarity for Next Location Prediction

다국어 초록 (Multilingual Abstract)

With the rapid development of social media, users' next location prediction has become an important research direction, which can provide personalized travel suggestions for users. However, existing methods ignore the semantic relationship between users' historical and current trajectories. This paper proposes a new method for predicting the user's next location to solve this problem. We first process the user POI data as trajectory data, use the attention mechanism to extract similar features of the user's historical trajectories, and then combine them with the current trajectory features to obtain the user's next location recommendation. The experimental results show that our proposed model performs satisfactorily on a real dataset.

목차 (Table of Contents)

• Abstract
• I. INTRODUCTION
• II. PROBLEM FORMULATION
• A. Definition
• B. Problem
• III. THE PROPOSED MODEL
• A. Embedding
• B. Trajectory Feature Extraction Module
• C. Trajectory Similarity Weighting Module
• D. Prediction module
• IV. EXPERIMENTAL RESULT
• V. CONCLUSION
• REFERENCES