Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Predicting taxi demand at high spatial resolution: Approaching the limit of predictability
Predicting Taxi–Passenger Demand Using Streaming Data
Utilizing Real-World Transportation Data for Accurate Traffic Prediction
Short-Term Forecasting of Passenger Demand under On-Demand Ride Services: A Spatio-Temporal Deep Learning Approach
(Blue) Taxi Destination and Trip Time Prediction from Partial Trajectories
Prediction of urban human mobility using large-scale taxi traces and its applications
Mining the Situation: Spatiotemporal Traffic Prediction With Big Data
Trip Fare Estimation Study from Taxi Routing Behaviors and Localizing Traces
Urban event detection with big data of taxi OD trips: A time series decomposition approach
Revealing daily travel patterns and city structure with taxi trip data
Riding from Urban Data to Insight Using New York City Taxis
Predicting Multi-step Citywide Passenger Demands Using Attention-based Neural Networks
Towards reducing taxicab cruising time using spatio-temporal profitability maps
Urban mobility study using taxi traces
Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data
Inferring Taxi Status Using GPS Trajectories
SemanticTraj: A New Approach to Interacting with Massive Taxi Trajectories
Mining Efficient Taxi Operation Strategies From Large Scale Geo-Location Data
Discovering and Characterizing Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data
A Taxi Gap Prediction Method via Double Ensemble Gradient Boosting Decision Tree
DeepSTCL: A Deep Spatio-temporal ConvLSTM for Travel Demand Prediction
introduction to probabilistic topic models .
Creating Diversity In Ensembles Using Artificial Data
The Science Of Self-Organization And Adaptivity
DroidMiner: Automated Mining and Characterization of Fine-grained Malicious Behaviors in Android Applications
phytoplankton control by grazing zooplankton : a study on the spring clear ‐ water phase1 .