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RE: Modeling information in an information rating system

in #hivemind3 years ago

A very interesting post.

However, the "coke" example is a very bad one. We all know that both (the product from Coca-Cola and Cocaïne) are bad for us, whether for the mind or for health. 😁

Regarding considering used-chosen tags on posts as useful information for domains, that's a step I probably wouldn't take. There are so many users who choose inappropriate tags, especially in order to get upvotes. Tags should first of all be compared to the content of the post whenever possible.

That said, this post allows me to glimpse the system you want to put in place and its huge potential to provide services for our platform. Now, I feel very excited and eager to read your next posts.

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To your point about tags, that's why I also mentioned this:

along with associated probabilities that the predicate actually belongs to each of the specified domains.

In other words, the tag originally assigned by the creator of the information can be rated as not applicable. Similarly other people could propose alternative tags that could then be rated.

Of course, none of the above argues against having an option for an automatic tagging system as a supplementary way to check (or even identify) domains as you're suggesting (and its ratings could also be rated by people). So here we could see cases where humans and AI are both checking each other's work.