It is good to be a data miner these days. Here is yet another opportunity to take part in a data mining competition. The focus of this one is to develop a predictive model based on shopping patterns. The patterns are largely comprised of contextual and behavioral data collected from users while surfing for products (and hopefully making purchases) on online shopping sites.
For this contest, Overstock.com is partnering with RichRelevance to develop improved algorithms that can suggest the best recommendations of products to present to their online shoppers while on the site. The recommendations are based on an initial model induced from collected past patterns. The model is continually improved and refined based on present patterns collected while the customer is shopping. The central idea is to essentially predict the customer's future behaviors on your retail website, thereby allowing your website to quickly present them with the items they are most likely shopping for in the first place. My understanding of the contest is that contest participants will need to work with the base RecLab code for the context, and data is suppled at the context website after registration. See the contest website for more details.
The award: $100,000 for each 1% performance improvement over their existing model, up to a maximum of $1,000,000 possible!
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