Learning Notes - Fashion Recommendation Papers

Paper - REDEFINING THE OFFLINE RETAIL EXPERIENCE: DESIGNING PRODUCT RECOMMENDATION SYSTEMS FOR FASHION STORES
Keynotes

• Leverage sensor technology, novel customer services
• Smart fitting rooms that offer garment recommendations

Attributes

• Sensor capabilities of smart fitting rooms
• Algorithms for Brick & Mortar recommendation systems
• Contextual attributes

Algorithms

• Content-based methods were similarities between item features are taken into account
• Collaborative-filtering approaches where product suggestions are based on the previous behavior of users with similar preferences

User cold start problem

• Using social media profiles to deduce customers’  preferences
• Adoption of association rule mining algorithms for product recommendations

Absence of explicit product ratings

• Propose combining them with clustering approaches
• Make association rules less generic and more customer-group-specific

Contextual Information in Brick and Mortar Stores

• Special attention must be paid to the selection of contextual attributes
• Location and time
• Trends and occasions
• User locations
• Customer interactions with products
• Store locations
• season, occasion, weather
• Categories activity (e.g., trying on garments)

Analysis of Data

• Patterns of buying across seasons

How to handle a cold start?
1. When customer attributes / product recommendation not available, use the popular item (Frequently bought from transactions)
2. Recommendations based on products customers bring into fitting rooms, Recommendations based on Apriori
3. Target individual customers if they identify themselves

Smart Mirror: Intelligent Makeup Recommendation and Synthesis

Key Notes - Model to generate/identify facial features, facial attributes, and makeup attributes recommendations
ML work

• Facial feature extraction - facial landmark point extraction
• Regions of Lips, eye, hair and face points extracted
• Makeup recommendation and synthesis. Recommendations based on eye shadow, skin color, and lip color
• Apply recommendations for eye, lipstick, hair color
• Apply makeup on the face

Keep Thinking!!!