Novelty and Diversity Metrics for Recommender Systems: Choice, Discovery and Relevance

Abstract

There is an increasing realization in the Recommender Systems (RS) field that novelty and diversity are fundamental qualities of recommendation effec-tiveness and added-value. We identify however a gap in the formalization of novel-ty and diversity metrics –and a consensus around them– comparable to the recent proposals in IR diversity. We study a formal characterization of different angles that RS novelty and diversity may take from the end-user viewpoint, aiming to con-tribute to a formal definition and understanding of different views and meanings of these magnitudes under common groundings. Building upon this, we derive metric schemes that take item position and relevance into account, two aspects not gener-ally addressed in the novelty and diversity metrics reported in the RS literature.