Exploring multi-list user interfaces for similar-item recommendations

Abstract

On many e-commerce and media streaming sites, the user interface (UI) consists of multiple lists of item suggestions. The items in each list are usually chosen based on pre-defined strategies and, e.g., show movies of the same genre or category. Such interfaces are common in practice, but there is almost no academic research regarding the optimal design and arrangement of such multi-list UIs for recommenders. In this paper, we report the results of an exploratory user study that examined the effects of various design alternatives on the decision-making behavior of users in the context of similar-item recommendations. Our investigations showed, among other aspects, that decision-making is slower and more demanding with multi-list interfaces, but that users also explore more options before making a decision. Regarding the selection of the algorithm to retrieve similar items, our study furthermore reveals the importance of considering social-based similarity measures.