Personalised Outfit Recommendations: Use Cases, Challenges and Opportunities

Recommender systems for fashion have gained in popularity in recent years. An exciting novel application for recommender systems is outfit personalisation. This work discusses the problem of personalised outfit recommendations and presents use cases, challenges and opportunities. This is still a nascent application area in many ways and there are opportunities for innovation in generating outfits, personalising them and displaying them in a coherent way to the user. Outfits are different from showing complimentary items (e.g. printer paper when you buy ink, socks when you buy shoes). Complimentary items are mostly about upselling the user to buy further items with their main purchase. Outfits can be that, but they are also about presenting the main item in different contexts. Showing the same dress in a work outfit, an evening outfit and a casual outfit showcases the use and value the user would get out of purchasing the dress (the main item). In retail words, outfits help sell the main item and are not necessarily about upselling the other items in the outfit as well. Outfits are often classified as complimentary item retrieval, however there are some important aspects of outfits that are closer to the concepts of contextual recommendations and full page optimisation (what things do you show next to each other). This extended abstract talks about the different use cases of outfits, gives an overview of the challenges in this domain, and presents scoped problem definitions that are the building blocks that need to be addressed in order to solve personalised outfits.