1. A method comprising: accessing at least one of an item listing title associated with an item listing of an e-commerce website and a user search query associated with an item search request submitted to the e-commerce website; converting words in the listing title or user search query to semantic tokens in a token symbol space, based on a tokenizing process; determining, using one or more processors, that one or more of the tokens are attribute values associated with predefined attributes of one or more product categories in a product category structure of the e-commerce website; classifying, using the one or more processors, remaining ones of the tokens as candidate product type tokens associated with a global product taxonomy; identifying frequent terms in leaf categories associated with the product category structure of the e-commerce website; determining an entropy value of each of the candidate product type tokens based on the frequent terms in the leaf categories; and ranking each of the candidate product type tokens, based on the entropy value associated with each of the candidate product type tokens.
4. The method of claim 1 , further comprising: classifying the highest ranked candidate product type token as a product type in the global product taxonomy; and incorporating the product type into the global product taxonomy.