# Automatically re-categorize topics from an imported forum by targeting keywords in titles?

**URL:** <https://meta.discourse.org/t/automatically-re-categorize-topics-from-an-imported-forum-by-targeting-keywords-in-titles/164663>\
**Category:** Migration\
**Created:** [September 20, 2020, 11:40pm UTC](https://meta.discourse.org/t/automatically-re-categorize-topics-from-an-imported-forum-by-targeting-keywords-in-titles/164663 "2020-09-20T23:40:12Z")\
**Posts on this page:** 1\
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**Author:** ![RGJ](https://sea3.discourse-cdn.com/meta/user_avatar/meta.discourse.org/rgj/32/523185_2.png) [@RGJ](https://meta.discourse.org/u/RGJ)\
**Post date:** [September 21, 2020, 9:57am UTC](https://meta.discourse.org/t/automatically-re-categorize-topics-from-an-imported-forum-by-targeting-keywords-in-titles/164663/3 "2020-09-21T09:57:44Z")

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I have previously approached similar projects by using unsupervised learning using K-means clustering. That would be a pretty cool experiment and maybe the algorithm even comes up with a better categorization 😉

You can read about such an approach here [https://towardsdatascience.com/applying-machine-learning-to-classify-an-unsupervised-text-document-e7bb6265f52](https://towardsdatascience.com/applying-machine-learning-to-classify-an-unsupervised-text-document-e7bb6265f52)

> [@Canapin](#):
>
> Do you have suggestions or ideas to minimize the risk of “false positives”?

Just like @EricGT said: don’t be afraid to iterate, but close enough is close enough, and maybe have some TL3 users ready to re-categorize where necessary.

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