18407455. COMPLEMENTARY APPAREL RECOMMENDATION SYSTEM simplified abstract (WALMART APOLLO, LLC)

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COMPLEMENTARY APPAREL RECOMMENDATION SYSTEM

Organization Name

WALMART APOLLO, LLC

Inventor(s)

He Wen of Menlo Park CA (US)

Sean Christopher D. Rosario of Sunnyvale CA (US)

Yanmin Liu of Bentonville AR (US)

COMPLEMENTARY APPAREL RECOMMENDATION SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18407455 titled 'COMPLEMENTARY APPAREL RECOMMENDATION SYSTEM

The patent application describes a system and method for recommending complementary apparel items based on an image of a model wearing a specific item of apparel.

  • Recommendation manager identifies the category of the complementary item.
  • Per-category similarity definition is used to identify category-specific features for determining similarity between items.
  • Pre-trained machine learning model calculates feature vectors representing the items.
  • Feature vectors are generated by concatenating feature vector values for category-specific features.
  • Candidates are ranked based on feature vector values to determine similarity.
  • Highest-ranking candidate items with the greatest degree of similarity are recommended to the user.
      1. Potential Applications:

This technology can be applied in e-commerce platforms, fashion styling apps, and virtual wardrobe assistants.

      1. Problems Solved:

This technology addresses the challenge of recommending complementary apparel items accurately based on visual cues.

      1. Benefits:

Users can receive personalized recommendations for apparel items that match their style preferences seamlessly.

      1. Commercial Applications:

"AI-driven Fashion Recommendation System for E-commerce Platforms"

      1. Prior Art:

Researchers can explore prior art related to machine learning models for fashion recommendation systems.

      1. Frequently Updated Research:

Researchers are continuously improving machine learning algorithms for better accuracy in recommending complementary apparel items.

        1. Questions about Fashion Recommendation Systems:

1. How does this technology improve the user experience in online shopping? 2. What are the key challenges in developing accurate fashion recommendation systems?


Original Abstract Submitted

Examples provide a system and method for recommending complementary apparel items based on an image of a model wearing an anchor item of apparel. A recommendation manager identifies the category of the complementary item. A per-category similarity definition is used to identify category-specific features used to determine whether a candidate item in the same category as the complementary item is the same or similar to the complementary item. A pre-trained machine learning model is used to calculate feature vectors representing the complementary item and each candidate item. The feature vectors are generated by concatenating feature vector values representing each feature in the plurality of category-specific features for the identified category. The candidates are ranked based on the feature vector values. The highest-ranking candidate items having the greatest degree of similarity to the complementary item are added to a list of recommended items presented to the user.

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