1. A method implemented by a default rating engine for estimating a default rating given to an item in a rated dataset by a reference user that has not yet explicitly rated that item, wherein said rated dataset comprises one or more series of ratings made by one or more respective users, each series comprising ratings of at least two items, said method comprising: recognizing a trigger for estimating said default rating; collecting an item average rating as the average rating given to said item by one or more users other than the reference user, a reference user average rating as the average rating given to other items by the reference user, and a dataset average rating as the average rating given to all items in the rated dataset by all users; generating a Poisson distribution of ratings given by the reference user on the basis of the reference user average rating, calculating a random Poisson rating on the basis of said Poisson distribution, and estimating said default rating by weighting said random Poisson rating on the basis of the item average rating, the reference user average rating, and the dataset average rating.