I want to apply unsupervised clustering on a set of short texts, which I need to divide into 2 clusters. Also I know that one of my clusters is likely to contain some words (non-exhaustive list) and I would like to use them for driving my machine learning.
I did not really find any simple way to do it (from any algorithm, library, tool...). Do you know one or have any solution to help me doing this?
I was thinking about applying some kind of k-means on my DTM matrix, using a specific metric e.g the euclidian distance between 2 texts which I would "artificially" reduce when the 2 texts words match my primary list of words which are likely to appear.
I did not test it yet and I was wondering if this solution could be relevant or not.