  Stemming is a process that can be utilized to trim inflected words to stem or
root form. It is useful for enhancing the retrieval effectiveness, especially
for text search in order to solve the mismatch problems. Previous research on
Bangla stemming mostly relied on eliminating multiple suffixes from a solitary
word through a recursive rule based procedure to recover progressively
applicable relative root. Our proposed system has enhanced the aforementioned
exploration by actualizing one of the stemming algorithms called N-gram
stemming. By utilizing an affiliation measure called dice coefficient, related
sets of words are clustered depending on their character structure. The
smallest word in one cluster may be considered as the stem. We additionally
analyzed Affinity Propagation clustering algorithms with coefficient similarity
as well as with median similarity. Our result indicates N-gram stemming
techniques to be effective in general which gave us around 87% accurate
clusters.
