I am trying to do some clustering. I have a dataset that is very sparse - with the majority of features only occurring in a single vector.
Here is a list of our features: https://gist.github.com/scrooloose/5963725dc88e5d15d74dcae522bebf82
I am looking for any suggestions/hints/pointers as to how we can merge some of these isolated features together. This should hopefully make my clustering experiments more successful.
For example, from a manual inspection of the data, I can see this group of features that could be all merged into a feature like "health" or perhaps "mental health" + "general health" or similar.
618: Mental Health Research 619: Mental disorder 1616: mental health 1617: mental illness 1618: men’s health 410: Genital wart 402: Genomic Medicine 476: Hygiene
Another example is this set of features that could be merged into something like "education":
536: Kiir Primary School 591: Makonzi Boarding School 609: Mathematics 670: New York University 300: Education 301: Educational psychology 349: Female education
Any thoughts would be very welcome, thanks :)
Side note: These features are keywords as returned from alchemy (http://www.alchemyapi.com/). Resulting from keyword searches for a set of URLS. The intention is to cluster the URLs (and hence they companies they represent) by these keywords.