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 describe the current landscape of research and expose our participants to real-world examples of item set recommendation. We further provide our audience with hands-on experience via a notebook session. Finally, we describe open challenges and call for further research in the area, which we hope will inspire both early stage and more experienced researchers.

Keywords:
Computer science Session (web analytics) Set (abstract data type) Recommender system Task (project management) Clothing Focus (optics) Information retrieval World Wide Web Data science Human–computer interaction Engineering

Metrics

4
Cited By
1.86
FWCI (Field Weighted Citation Impact)
23
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Recommender Systems and Techniques
Physical Sciences →  Computer Science →  Information Systems
Consumer Market Behavior and Pricing
Social Sciences →  Business, Management and Accounting →  Marketing
Data Visualization and Analytics
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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