improved avaluation by precalculating and caching numRecomms array which contains all the transition numbers according to the number of recommendations (e.g. N=5)
implemented cluster pruning and trans matrix pruning
changed recommendation strategy to:

recommend clusters' most popular items
implemented new item choice strategy:

choose items that appear most often within the cluster