Review and synthesis of expert perspectives on user attribute and profile definitions for fashion recommendation

ABSTRACT

A key obstacle in personalised fashion recommendations is the challenge of capturing user physical attributes at a large scale, which limits exclusively computational methods (like machine learning) to readily available attributes whose influence on recommendation accuracy is variable. Expert advice is a potential means of identifying influential user attributes. However, individual experts often disagree or offer conflicting advice. Thus, identifying areas where expert advice is or isn't consistent, in the context of user attributes and profiling is critical. Here, we characterise the breadth of expert definitions of user attributes and profiles through an exhaustive assessment of 156 years of advice literature. Expert definitions of body colouring, shape, and personality attributes are extracted and compared. The range of attribute-value relationships and profile definitions in each domain is described, and coherence among authors for each domain is discussed.

KEYWORDS:

• Fashion recommendation
• clothing recommendation
• fashion advice
• feature engineering
• user profiles

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by University of Minnesota Sustainable Development Goals Initiative.; US National Science Foundation: [grant number #1715200].