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I am working on a webapp (fullstack JS) where the user create documents and attach tags to them. They also select a list of tags they are interested in and attach them to their profile.

I am not a math guy, but I did some NLP as hobbyist and learnt about latent semantic indexation: as I understand it, you create a table where you store each couple of words you parsed, and then add weight to each of these couples of words when both are found next to each other.

I was thinking of doing the same thing with tags: when 2 tags appear on the same document or profile, I increase the weight of their couple. That would allow me to get a ranking of the "closest" tags of a given one.

Then I remembered that I came across web graphs, where websites were represented in a 2D space (x and y coordinates) and placed depending on their links using an algorithm called force vector.

While I do know how I would implement my first idea, I am not sure about the second one. How do I spread the tag coordinates when created? Do they all have an x:0, y:0 at the start?

Since I assume this is a common case of data sorting, I wondered what would be the common/best practices recommended by people of the field.

Is there documents, articles, libraries (npm?) or wikipedia pages you could point me out to help me understand what can or should ideally be done? Is my first option a good one by default?

Also, please let me know in comments if I should add or remove a tag to this question or edit its title: I'm not even sure of how to categorize it.

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