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Small Sample Travel Feature Inference Based on Multi-Clustering Topic Model Over Internet of Things
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Normalized Approach to Find Optimal Number of Topics in Latent Dirichlet Allocation (LDA)
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Sampling-based epoch differentiation calibrated graph convolution network for point-of-interest recommendation
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Robust deep k -means: An effective and simple method for data clustering
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Knowledge discovery using an enhanced latent Dirichlet allocation-based clustering method for solving on-site assembly problems
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Optimization of bus stop placement for routes on uneven topography
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User Profiling for Tourist Trip Recommendations using Social Sensing
inferredcites →https://doi.org/10.1109/jiot.2019.2955102openalex-extracted
IoT-Based Context-Aware Intelligent Public Transport System in a Metropolitan Area
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Data and Knowledge Twin Driven Integration for Large-Scale Device-Free Localization
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The Study of Urban Residential’s Public Space Activeness Using Space-Centric Approach
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A Push-Based Probabilistic Method for Source Location Privacy Protection in Underwater Acoustic Sensor Networks
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Privacy-Aware Point-of-Interest Category Recommendation in Internet of Things
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Robust Network-Wide Bus Scheduling With Transfer Synchronizations
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A Fast Adaptive k-means with No Bounds
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SimpleMKKM: Simple Multiple Kernel K-Means
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A guided latent Dirichlet allocation approach to investigate real-time latent topics of Twitter data during Hurricane Laura
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Research on the Allocation of Urban and Rural Public Service Facilities Based on Life Circle Theory—A Case Study of Honghu City, Hubei Province
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