Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Improving Demand Prediction in Bike Sharing System by Learning Global Features
Data analysis and optimization for (citi)bike sharing
Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China
Incentivizing users for balancing bike sharing systems
analysing bicycle sharing system user destination choice preferences : an investigation of chicago ’ s divvy system .
Mining the Situation: Spatiotemporal Traffic Prediction With Big Data
Predicting Taxi–Passenger Demand Using Streaming Data
Utilizing Real-World Transportation Data for Accurate Traffic Prediction
DeepSTCL: A Deep Spatio-temporal ConvLSTM for Travel Demand Prediction
Dynamic Bike Reposition: A Spatio-Temporal Reinforcement Learning Approach
Transfer Learning for Traffic Speed Prediction with Effective Spatiotemporal Features
SHARED BICYCLES IN A CITY : A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE
On Learning Prediction Models for Tourists Paths
Traffic Flow Prediction With Big Data: A Deep Learning Approach
Predictive routing for autonomous mobility-on-demand systems with ride-sharing
A heuristic algorithm for a single vehicle static bike sharing rebalancing problem
Exploiting Heterogeneous Human Mobility Patterns for Intelligent Bus Routing
Inferring Dockless Shared Bike Distribution in New Cities
Adaptive Personalized Travel Information Systems: A Bayesian Method to Learn Users' Personal Preferences in Multimodal Transport Networks
Mining User Mobility Features for Next Place Prediction in Location-Based Services
Predicting driver maneuvers by learning holistic features
A low-voltage low-power fully differential rail-to-rail input/output opamp in 65-nm CMOS
web - scale bayesian click - through rate prediction for sponsored search advertising in microsoft ' s bing search engine .
Music type classification by spectral contrast feature
Semantic classifications for detection of verb metaphors
Secure Virtual Machine Execution under an Untrusted Management OS