Can someone explain to me how the “Relevance” ranking works when you search for something?
This is just a theory on makerworld theory, I still miss him. Don’t quote me, but my best assumption is that Relevance algorithm works by finding common tags in your recently viewed and favorites. Then find models which have these tags. This might not be correct, correct me if I am wrong
The paramount factor, unequivocally, lies in the alignment between the search term and the title. When you search for a brief term (e.g., a single word) and contrast it with a pre-filtered roster of models featuring that word in either the title or description, the ones boasting shorter titles typically emerge victorious or attain top rankings. This phenomenon extends to the extent that models with the search term in the title may succumb to others where the term only appears in the description or tags.
In essence, it’s a deeply flawed system that is susceptible to significant exploitation.
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Thanks for the explanation Uhl.