Consider a talent pool in which each member has some set of skills. Some of these talent are submitted to orders as potential candidates of which one is selected. It is reasonable to assume that the submitted talent have some dominant thing in common in their skill sets (let's call it a segment) that qualifies them for the order. Example segments are front end web-designer or brochure / sprint designer.Given the total set of skills over all of the talent submitted to an order (like 2-5 with say 10 skills each, so 20 - 50 skills total), I am looking for the dominant segment. Then, I am looking for the dominant segment for each individual talent.My plan is to use latent Dirichlet allocation (LDA) such that the skills of all the talent submitted for an order are a document that contains some segments or topics with some probability. Likely, there will be one or two dominant topics depending on the total topic number. I will then use this model to predict the dominant segment for each talent where the individual talent skill set is a document with some segments or topics within.I am curious if anyone has feedback about my use of LDA or other ideas about how I might go about discovering these segments?
Different methods for clustering skills in text
machine learning;data mining;nlp;text mining