In an effort to increase user engagement, satisfaction, and profitability, many websites are offering their users various types of recommendations. Many people are familiar with Amazon.com’s people who bought also bought or people who browsed also browsed. But how do they do that?
Darren Vengroff, chief scientist from RichRelevance, explains some of the components of a recommendation system in a GigaOM article.
Netflix just implemented some updates to their star rating predictions based on some work done on the Netflix Prize. Here’s what Todd Yellin, Director of Product Management, and Jon Sanders, Director of Recommendation Systems have to say on the Netflix Blog.
The NY Times has an article discussing how models can help predict the spread of the flu.
If you’re looking for a good explanation of Bayes’ theorem, relating the conditional and marginal probabilities of two random events, this blog post does a great job through the use of visuals.
Greg Linden put together a few thoughts about recommendation algorithms. His ideas continue at a post on the Communications of the ACM Blog.
Read Write Web compiled some information about recommendation engine provider, Choicestream, and what they can do for online advertising.
Predictive analytics software vendor, KXEN, has announced two upcoming training sessions to be held in Chicago.
Check out their newsletter and archives.
Prediction Impact offers predictive analytics training seminars
Here’s an interesting textbook - Introduction to Probability Models
