In last week’s blog, I outlined how plista’s RecommendationAds work- namely through combining interested-based filtering and various data vectors in order to come up with the personalized content recommendations the user sees on the page he or she is browsing. To put it more accurately, we use recommender algorithms for the interest-based filtering process. We at plista believe that we currently have one of the best live recommender algorithms out there, proven time and again by the success of our ad formats; average CTR (Click Through Rate) for the RecommendationAds alone is over 7%.

However, in order to continue to improve our services, we’d like to see how our recommender algorithms would compare to any contenders. We have therefore launched a contest to find the best live recommender algorithm to compete with our own. There is a weekly prize of 100 € for the best-performing team, and an exclusive grand prize (details of which are still to be announced) which will be awarded to the best-performing team overall over an extended period of time.

The aim of the contest is to improve the performance of the on-screen recommendation widgets that plista provides, which come in the format “you might also find this interesting”. Performance is measured by the CTR- the amount of clicks per number of displays for a given set of recommendations- as well as the response time for each recommendation request.

The contest consists of two rounds for each team: the preliminary round, where teams receive a low volume of messages with a chance of winning the weekly prize and qualifying themselves for the second stage, where the teams receive a much higher volume of messages and the chance of winning the elusive grand prize. Interested? Then read the introduction and take a look at the contest Wiki too for more information. Have you got what it takes?

Spread and share with your friends on Twitter and Facebook – maybe one of them will be the winner of the grand prize!

Find out more: http://contest.plista.com/