gong yongshun
Professor
Yongshun Gong is a Professor in the School of Software, Shandong University. He received his Ph.D. degree from University of Technology Sydney in 2020. He has got the support by Natural Science Foundation of Shandong Province for Excellent Young Scholars. His principal research interest covers data science, representation learning and machine learning, particularly in the areas of representation learning, spatio-temporal data mining, predictiv... More+
Paper Publications
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[1] 陈勐. Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spat.... 2024.
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[2] 孙天骜. Going Where, by Whom, and at What Time: Next Location Prediction Considering User Preference and .... 2024.
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[3] 张大滨. Exploring Urban Semantics: A Multimodal Model for POI Semantic Annotation with Street View Images.... 2024.
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[4] 贾宏伟. Learning Hierarchy-Enhanced POI Category Representations Using Disentangled Mobility Sequences. 2024.
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[5] 张欣欣. Spatio-Temporal Multi-Image Reflection Removal. IEEE Signal Processing Letters, 31, 2345, 2024.
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[6] 李晓宇. Dual-track spatio-temporal learning for urban flow prediction with adaptive normalization. ARTIFICIAL INTELLIGENCE, 2024.
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[7] . Spatio-temporal fusion and contrastive learning for urban flow prediction. Knowledge-Based Systems, 2023.
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[8] . Mask- and Contrast-Enhanced Spatio-Temporal Learning for Urban Flow Prediction. 2023.
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[9] 王瑞丰. Fine-grained Urban Flow Inference with Unobservable Data via Space-Time Attraction Learning. 2023.
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[10] 黄瑾. Focusing on Subtle Differences: A Feature Disentanglement Model for Series Photo Selection. IEEE transactions on multimedia, 2024.
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[11] 张欣欣. Two-phase Parametric Registration for Retinal Images. 2024.
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[12] 王梦怡. Personalized Single Image Reflection Removal Network through Adaptive Cascade Refinement. 2023.
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[13] 黄瑾. Modeling Multiple Aesthetic Views for Series Photo Selection. IEEE transactions on multimedia, 2023.
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[14] 宫永顺. Latent evolution model for change point detection in time-varying networks. Information Sciences, 2023.
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[15] 宫永顺. Missingness-Pattern-Adaptive Learning With Incomplete Data. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023.
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[16] 邴俊翔. Pre-trained Semantic Embeddings for POI Categories Based on Multiple Contexts. IEEE Transactions on Knowledge and Data Engineering, 2022.
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[17] 徐榕荟. TME: Tree-guided Multi-task Embedding Learning towards Semantic Venue Annotation. ACM Transactions on Information Systems (TOIS), 41, 2023.
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[18] 曲浩. Forecasting Fine-grained Urban Flows via Spatio-temporal Contrastive Self-Supervision. IEEE Transactions on Knowledge and Data Engineering, 1, 2022.
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[19] 贺甜甜. Exploring Linear Feature Disentanglement For Neural Networks. 2022.
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[20] 黄瑾. Series Photo Selection via Multi-view Graph Learning. 2022.