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Multi-View Contrastive Learning for Sequential Recommendation
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Modeling User Behaviors in Online Systems and Ubiquitous Devices
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Entity Identification Based on Human Mobility Data
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Automatic Emotion Detection in Text Messages using Supervised Learning
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Modeling Heterogeneous Users Behaviors in Online Systems
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Detecting and Mitigating the Spread of Low-Quality Information in Social Media
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Automated Fact Extraction and Verification for Detecting False Information
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Unsupervised Semantic Segmentation through Cross-Instance Representation Similarity
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Attributed Multi-Relational Attention Network for Fact-checking URL Recommendation
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Detecting Various Types of Malicious Users at One Sitting in Online Social Networks
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