Hi, Consider this as a newbie question.
I have been reading about CF algorithms. Everyone seems to be taking the preference value as ratings, or any singular attribute. However, in a typical ecommerce scenario the entire clickstream data is important ( with varying weights) to determine the affinity of the user vs item. So, my question is, in production, do we consider many such parameters to calculate user vs item affinity or do we just pick any one parameter. If we pick any one parameter, how do we decide which is the one that will reflect the affinity in the best possible way? If we consider many parameters, do we use any kind of a regression to formulate the affinity score (that takes into consideration all the features and their respective weights that impact the users liklehood) and run any CF algorithm over these scores? Thanks. -- Best Regards, Jayesh
