Automated extraction, inference and normalization of structured attributes for product data

A system comprising:

• one or more processors;
• and
• a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:
• defining a product-description taxonomy represented according to a classification tree comprising clustering tags using product data from product records in a product catalog, the classification tree comprising at least one product category path defined by one or more product category nodes at successively deeper tree levels, at least one product category node associated with at least one product attribute-key paired with one or more key-values;
• defining key data using the product data, the key data comprising:
• at least one product attribute-key,
• one or more allowed key-values, and
• a representative key-value corresponding to a set of equivalent key-values;
• defining heuristic data using the product data and the key data, the heuristic data comprising:
• a mapping between a product attribute-key and a set of equivalent attribute-keys, and
• at least one key-value exclusive to a particular product attribute-key;
• and
• applying:
• one or more machine learning (ML) models, and
• the key data, and/or heuristic data, the heuristic data defined using the product data and the key data, the heuristic data comprising a mapping between a product attribute-key and a set of equivalent attribute-keys,
• to an input product record to generate an output normalized product record categorizing the input product record according to the classification tree's product-description taxonomy.