Simple (naive) document clustering using tf-idf and k-mean

When i developed this blog (using my own client-server platform such as web server, back-end, front-end, etc., built from ash/scratch :) ), i simply designed it as a simple "note book" where i put my ideas or some stuffs that i have done. So, initially, there are no category no advance feature like post suggestion based on current post, etc. It is just a bunch of posts sorting by date. The thing is, i usually work on many different domains (robotic, IoT, backend, frontend platform design, etc.), so my posts are mixed up between different categories. It is fine for me, but is a real inconvenience for readers who want to follow up their interesting category on the blog. Of course, i could redesign the blog and add the missing features by messing around with the relational database design (i'm using SQLite btw), manually classifying the posts in the back-end, etc. But, i'm a kind of lazy people, so i've been thinking of a more automatic solution. How about an automatic document clustering feature based on a data mining approach ? Here we go!

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