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Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Dongbo Xi, Fuzhen Zhuang, Bowen Song +6
Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular…
Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3
Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…
Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction
Qiang Zhou, Jingjing Gu, Xinjiang Lu +4
Potential crowd flow prediction for new planned transportation sites is a fundamental task for urban planners and administrators. Intuitively, the potential crowd flow of the new c…
Combat Data Shift in Few-shot Learning with Knowledge Graph
Yongchun Zhu, Fuzhen Zhuang, Xiangliang Zhang +4
Many few-shot learning approaches have been designed under the meta-learning framework, which learns from a variety of learning tasks and generalizes to new tasks. These meta-learn…