Exploiting Regression Trees as User Models for Intent-Aware Multi-attribute Diversity.

Diversity in a recommendation list has been recognized as one of the key factors to increase user’s satisfaction when interacting with a recommender system. Analogously to the modelling and exploitation of query intent in Information Retrieval adopted to improve diversity in search results, in this paper we focus on eliciting and using the prole of a user which is in turn exploited to represent her intents. The model is based on regression trees and is used to improve personalized diversication of the recommendation list in a multi-attribute setting. We tested the proposed approach and showed its eectiveness in two dierent domains, i.e. books and movies.