Efficient optimization of multiple recommendation quality factors according to individual user tendencies

An efficient post-processing scheme for recommendation lists is proposed.It can adjust quality factors, like diversity, of a list to match user tendencies.Compromises on accuracy are kept low.The method is compared with other post-processing algorithms from the literature.It can be used to build novel fine-grained personalization approach...More