Taxonomy categorization involves training a model to perform product classification in a hierarchical manner, i.e. one producing a taxonomy structure or tree with a root, middle nodes, and leaf nodes. For example, one might have the goal of categorizing cookware into increasingly refined categories such as Cookware -> (Pots, Pans) -> (Stew Pot, Sauce Pan), etc. Many types of products can be categorized into a taxonomy.
In machine learning, product categorization is a method of classifying products based on predefined parameters, making them easier to recognize for the users and improving search results.
To provide more efficient buying and selling experiences on online shopping sites, it is important for machine learning systems to understand relevant products for genders. Experts train the ML algorithm to predict gender.
Object categorization from image search is a challenging task where machine learning models are trained to recognize and assign specific objects to a certain category. This process is sometimes called generic object categorization.