Liftago On-Demand Transport Dataset and Market Formation Algorithm Based on Machine Learning

August 09, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Jan Mrkos, Jan Drchal, Malcolm Egan, Michal Jakob arXiv ID 1608.02858 Category cs.AI: Artificial Intelligence Cross-listed cs.CY Citations 1 Venue arXiv.org Last Checked 4 months ago
Abstract
This document serves as a technical report for the analysis of on-demand transport dataset. Moreover we show how the dataset can be used to develop a market formation algorithm based on machine learning. Data used in this work comes from Liftago, a Prague based company which connects taxi drivers and customers through a smartphone app. The dataset is analysed from the machine-learning perspective: we give an overview of features available as well as results of feature ranking. Later we propose the SImple Data-driven MArket Formation (SIDMAF) algorithm which aims to improve a relevance while connecting customers with relevant drivers. We compare the heuristics currently used by Liftago with SIDMAF using two key performance indicators.
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