Personalized Recommender System based on Taxi Driver’s Behavior to Optimize Supply and Demand, M.Sc. Thesis Sharif University of Technology ; Heydarnoori, Abbas (Supervisor) ; Habibi, Jafar (Co-Advisor)
Abstract
Taxis provide a flexible and indispensable service to satisfy the urban travel demand of public commuters. Balancing supply and demand and minimizing the driving time before finding a customer would directly increase taxi drivers and system income. Availability of GPS traces and easy access to the Internet has enabled taxi companies to be aware of supply-demand level in every region and all taxi states in real time. In this research, we propose a novel fair recommender system to maximize the sum of taxi drivers’ income by recommending regions with the highest profitability due to each driver’s acceptance rate and each regions’ minimum supply availability. Experiment results on TAP30’s data...
Cataloging briefPersonalized Recommender System based on Taxi Driver’s Behavior to Optimize Supply and Demand, M.Sc. Thesis Sharif University of Technology ; Heydarnoori, Abbas (Supervisor) ; Habibi, Jafar (Co-Advisor)
Abstract
Taxis provide a flexible and indispensable service to satisfy the urban travel demand of public commuters. Balancing supply and demand and minimizing the driving time before finding a customer would directly increase taxi drivers and system income. Availability of GPS traces and easy access to the Internet has enabled taxi companies to be aware of supply-demand level in every region and all taxi states in real time. In this research, we propose a novel fair recommender system to maximize the sum of taxi drivers’ income by recommending regions with the highest profitability due to each driver’s acceptance rate and each regions’ minimum supply availability. Experiment results on TAP30’s data...
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