"If the system flags a product with a low level of confidence, meaning that it is unsure if the attributes it attached are a perfect match, the taxonomists can supplement the machine."

If the machine didn't figure it out, the human can provide the missing knowledge
“Taxonomy is always growing. It's a living, breathing set of information"

Every new input that the human adds is part of the taxonomy and the overall systems gets better and better
“In fashion, there are so many ways of describing the same thing, which is quite nuanced and is quite internal to the industry, but can be a problem for our customers,”

Problem that appears in all industries! One word means multiple things. Or multiple words mean the same thing
"Garments that arrive at Farfetch are described, photographed and “editorialised” manually; the product’s taxonomy is then enriched automatically using a fashion knowledge graph created by Farfetch data scientists working with its fashion experts."
"[the knowledge graph] stores thousands of descriptive fashion terms that have relationships associated with them, which helps in the product recommendation process."

One of the use cases for knowledge graphs is for product recommendation
"...while there are still some traditional fashion taxonomists on the team, that function is increasingly merging with the duties of data scientists."

Data Scientists need to learn more about semantics, taxonomies, ontologies and knowledge graphs!
"AI-enhanced taxonomy can better identify products on a spectrum, rather than in binary terms"

Semantics help understand the gray areas
"Tech-informed taxonomy can also help in resale. Unlike sneakers, which include standardised style codes, luxury brands do not use standardised or public taxonomy."

Adding standardize codes (i.e. semantics) makes like easier... and can help you make money
"In the immediate term, sophisticated taxonomies mean consumers will be better able to find what they want online, with less time and effort."

Semantics help the consumers, not just the business. Google started to show this with their Knowledge Graph in 2012!
"But it will take considerable investment to get there, particularly for retailers that are less advanced in areas like data science and AI."

The path is not easy, but definitely valuable. If you need help, have questions, reach out. I live this every day!
You can follow @juansequeda.
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