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I added two links in the references to general categories used in advertising and NLP. They are hierarchical with the lowest layers probably too fine-grained, but the higher layers could be good categories to provide canned labels for users searching for domain-specific datasets.
Other important labels include: synthetic, training, tuning, materials, healthcare, time series, science, math, tech, audio, video, multimedia, language, particular languages, etc.
The text was updated successfully, but these errors were encountered:
I added two links in the references to general categories used in advertising and NLP. They are hierarchical with the lowest layers probably too fine-grained, but the higher layers could be good categories to provide canned labels for users searching for domain-specific datasets.
Other important labels include:
synthetic
,training
,tuning
,materials
,healthcare
,time series
,science, math, tech
,audio
,video
,multimedia
,language
, particular languages, etc.The text was updated successfully, but these errors were encountered: