What machine learning algorithms are used for internet advertising? I.e. based on stats of site visiting, clicks, classifying visitors based on what they are interested in, time, day of week etc.
Any frameworks/resources you can recommend?
For example: we have a lot of advertisements with different prices. Task is to build a set of advertisements in a block to achieve the best CTR (in other words we need to show what people click)
 A: I'm trying to read between the lines of your question ad to find a practical approach to the problem behind:
1. from methodological point of view you need to be good in design of experiments; a good book (a bible) on this topic is Design and Analysis of Experiments by Douglas Montgomery; Minitab (proprietary software) is very versatile and friendly on this but also R is very good (e.g please see package "agricolae")
2. from technical point of view, for a practical implementation the free tool Google Web Optimizer is a good starting point; it allows you to implement and feed with data the the research; (you can us it complementary with Google Analytics)
This approach is not only for advertising; this two ingredients allows you to plan and implement strategic research via web e.g segmentation of web customers, targeting, pricing analysis etc. 
All above can be just a stating and background point; to scale you will need a home brewed methodological approach and technical stuff (e.g research plan, proper experimental designs and analysis; also on software side: specialized web cookies, a MongoDB database or whatever to log data in efficient way, and all of these just to solve your formulated business questions).
NB: IMHO "machine learning" is not the best word in your question and not a feasible answer to the problem.
Cheers,
Marius
