The Practical Quant Blog, BEN LORICA, December 2, 2010
Given the increasing demand for data scientists, it might not be a bad idea for companies to reach out to the top contestants in some of these competitions. Below are a few contests that caught my eye over the past few weeks. I'm not surprised that direct marketing is a popular source of contest topics -- the direct marketing industry has held analytics contest for years. It is interesting to see geo-location, navigation, and traffic prediction emerge as another popular domain.
2010 UC San Diego Data Mining Contest: Winning entries from the U.S., India, Canada, South Korea, and Russia.
In this year's contest, an online retailer is interested identifying potential new customers from a population of consumers. Your task is to rank ordering consumer pool according to who is most likely to become customers of the retailer.
World Economic Forum Data Visualization Challenge: The contestants faced a pretty challenging task, and unless you're familiar with the different bureaucracies involved, the resulting visualizations are still hard to grok.
The Hearst Challenge (optimize distribution to newstands): Co-sponsored by the Hearst Corporation, the Direct Marketing Association, and EXL, this contest "has closed to new registrations", but registered contestants can continue to submit entries until December 4th.
Over the years, the magazine publishing industry has made significant strides in improving subscription based circulation by developing analytic frameworks that better predict customer response to acquisition and renewal offers. The objective of this contest is to apply the same analytic discipline and effectively predict newsstand locations "response". Specifically the objective is to predict the number of copies to be placed in each newsstand location to optimize the overall contribution of the newsstand location typically referred to as draw.
2010 Direct Marketing Association Analytic challenge. Datalab USA using software from Salford Systems produced the winning entry.
Build the best targeting solution for lapsed donor segments.
The contestants devised algorithms for three tasks: (1) Traffic congestion prediction, (2) Modeling the process of traffic jams formation during morning peak in the presence of roadworks, and (3) Traffic reconstruction and prediction based on real-time information from individual drivers. Winning entries were from the U.S. and Europe.
Sponsored by the ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD), this annual contest uses challenging problems from a variety of domains. The 2010 challenge was from Mathematics Education.