Abstract
A novel unsupervised learning approach to computational dialectometry is presented which
uses hard clustering. The approach relies on vector analysis over two-dimensional arrays
of word lists collected for different geographical sites. The paper presents the underlying
theory and applies the approach to a Bulgarian data set. The results of these experiments
demonstrate the viability
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