Abstract

In this tutorial, we aim to shed light on the task of recommending a set of multiple items at once. In this scenario, historical interaction data between users and items could also be in the form of a sequence of interactions with sets of items. Complex sets of items being recommended together occur in different and diverse domains, such as grocery shopping with so-called baskets and fashion set recommendation with a focus on outfits rather than individual clothing items. We will introduce the problem of complex item set recommendation and describe the current landscape of research. We will provide the audience with hands-on experience via a notebook session, outline open challenges and call for further research in the area.

Organizers

• Mozhdeh Ariannezhad
• Sami Jullien
• Ming Li
• Maarten de Rijke

Materials

In due course, we will add the following materials: slides, notebooks (for a guided lab session), pre-trained models (to allow attendees to focus on inference and result interpretation during the hands-on session), an annotated bibliography, and code.