Interestingness is quite complex, and those studies seem to be about absolute interestingness. I wonder what predictors would determine relative interestingness

Interestingness is quite complex, and those studies seem to be about absolute interestingness. I wonder what predictors would determine relative interestingness. For example, given a set of articles that a person found interesting in the past how well could you predict that some new article will be interesting to that person? How well could you predict that given articles their friends found interesting? What about articles that came from a source that produced interesting articles in the past, or articles that were tagged with the same words, and so on. Furthermore, what algorithm would be best? A type of Bayesian filtering is really effective at separating spam from non-spam, would it be effective at filtering interesting from non-interesting?