1. A computer-implemented method for determining relevance for a user between a predictor item of content and a plurality of target items of content, said method comprising: storing, in data storage, at least one weight parameter for said target items that measures similarity of content between a target item and said predictor item; storing an affinity score for each of said target items relative to said predictor item, that measures a correlation between said predictor item and said corresponding target item based on interests of a plurality of users; setting at least one user preference parameter that indicates similarity, including more similar and less similar, desired by said user for content relative to said predictor item; processing, in a computer, to determine relevance of said target items of content for said user by generating a final score by: multiplying said weight parameters on similarity for said target items with said user preference parameter for more similar or less similar to generate a user modified similarity score; adding said affinity score for each of said target items to said modified similarity score for each of said target items to generate said final score for each of said target items; and determining relevance of said target items of content for said user based on said final score for said target items.