1. why not use the other columns as evidences and come up with a preference
score and see if results improve.. May be you
use other machine learning algorithms to generate such preference
scores...
2. one other way may be to implement a custom similarity Score and not the
ones that ships wit
I figured out how to parse csv files and use a map of Userid,item id and
build a normal recommender,which gives user a recommendation of some items.
Although this method isn't able to utilize all my data considering its only
using two columns.
I have multiple different columns such as category,sh
