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Creative AIML Datasets

1 点作者 profsummergig大约 1 个月前
I just read about how, to train AIML to do sentiment analysis, some projects use Amazon reviews for data.<p>See, every Amazon review has to be accompanied by a star rating. if the star rating is poor, then the accompanying text is likely to be negative. And vice versa.<p>Blew my mind.<p>It&#x27;s totally self-contained. No need to hire humans in Kenya or India to rate a piece of text to determine and label its sentiment.<p>I thought this was a highly creative way to approach the &quot;data problem&quot;.<p>I want to learn more about such creative solutions to the &quot;data problem&quot;.<p>Please share what you know about such creative solutions (or your ideas on creative solutions to the &quot;data problem&quot;) on this page so we can have a resource to reference.<p>Thank you.

1 comment

bigyabai大约 1 个月前
FWIW Google Bert has been doing sentiment analysis with LLMs using text classifiers for more than 7 years at this point: <a href="https:&#x2F;&#x2F;github.com&#x2F;google-research&#x2F;bert">https:&#x2F;&#x2F;github.com&#x2F;google-research&#x2F;bert</a><p>It&#x27;s definitely a neat solution, but a pretty old one at this point. Those AWS Mechanical Turk employees lost their job a half decade ago, chances are.