SmartAdP: Visual Analytics of Large-scale
Taxi Trajectories for Selecting Billboard Locations

The interactive user interface of the SmartAdp system. An online system of SmartAdP has been deployed here.

The problem of formulating solutions immediately and comparing them rapidly for billboard placements has plagued advertising planners for a long time, owing to the lack of efficient tools for in-depth analyses to make informed decisions. In this study, we attempt to employ visual analytics that combines the state-of-the-art mining and visualization techniques to tackle this problem using large-scale GPS trajectory data. In particular, we present \name, an interactive visual analytics system that deals with the two major challenges including finding good solutions in a huge solution space and comparing the solutions in a visual and intuitive manner. An interactive framework that integrates a novel visualization-driven data mining model enables advertising planners to effectively and efficiently formulate good candidate solutions. In addition, we propose a set of coupled visualizations: a solution view with metaphor-based glyphs to visualize the correlation between different solutions; a location view to display billboard locations in a compact manner; and a ranking view to present multi-typed rankings of the solutions. This system has been demonstrated using case studies with a real-world dataset and domain-expert interviews. Our approach can be adapted for other location selection problems such as selecting locations of retail stores or restaurants using trajectory data.

@article {DLiu2016,
author = {Dongyu Liu and Di Weng and Yuhong Li and Jie Bao and Yu Zheng and Huamin Qu and Yingcai Wu},
title = {{SmartAdp}: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations},
journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE VAST 2016},
year = {2014},
volume = {20},
number = {12}
}

The work is supported by National 973 Program of China(2015CB352503), the Fundamental Research Funds for Central Universities (2016QNA5014), National Natural Science Foundation of China (No. 61502416), the research fund of the Ministry of Education of China (188170-170160502), 100 Talents Program of Zhejiang University, RGC GRF16241916, ITS/170/15FP, and a grant from Microsoft Research Asia.