Prescriptive Analytics for the Physical World (PAPW 2020)
Workshop held in conjunction with KDD 2020
Prescriptive analytics focuses on analyzing data in order to find the best policy to prevent a disaster (e.g., disease pandemic) or to mitigate a problem (e.g., traffic congestion), and then on prescribing the best actions to implement such a policy in the physical world and/or to study the impact of the implementation of such a policy on the physical world. Encompassing both descriptive analytics and predictive analytics, prescriptive analytics goes beyond by providing actionable insights.
In the data mining research today, however, we see that problems related to prescriptive analytics, especially those problems in the physical world, remain largely unexplored. Take the application in transportation for example. We saw enormous research studies related to problems such as traffic prediction and traffic outlier detection. However, we see little work in terms of how to actually make traffic less congested by taking certain actions (e.g., better traffic signal control strategies or traffic restriction rules). For another example, in epidemic data analysis, we often see research studies to forecast how epidemics spread, but we seldom see data-driven solutions about how to implement policies (e.g., quarantine, public transportation) so that we can minimize the spread of epidemics, and how to study the impact of the implemented policies on the environment as a whole.
In this workshop, we would like to ask this critically important question: how could we learn from the data in order to take better strategic actions in the real physical world?
Topics of interest include but not limited to:
Our workshop will have an exciting program with world-wide researchers and practitioners to share their research and experience about how to turn data into actions in the physical world. We will invite keynote talks, paper presentations, and panel discussions. We will not have workshop paper submission.
Practice round provides one scenario of 10K-people for 60 days.
Official competition has five different scenarios, each simulates 10K-people for 60 days.