This restores previous behavior, where a cluster primary artist is based on the tokenized artist name, but then the most common real spelling is being used.
The existing code was using the Levenshtein distance to calculate similarity, which caused a O(n^2) performance. But since only exactly similar matches where used (similarity threshold 1.0) this was not necessary.
This new implementation uses simple comparison for string equality and performs in O(n).
