I am working on a text processer which gives out similarities between a set of strings. After weighted LCS, Levenshtein distance and double metaphone matching, I get buckets of strings such as Bucket for string $i \rightarrow [s, k, m]$Bucket for string $j \rightarrow [i, s, k]$This effectively implies that $i,j,s,k,m$ belong to the same cluster.One of the ways I could do this is to build a connectivity graph and cluster all the connected components.The other way is to iteratively check for the matches.Could somebody help me do it better.
A better way to cluster items
graph algorithms;clustering;data mining