First, a crude similarity measure between wordlists, based on Levenshtein distance, was defined and the 1% of all ASJP doculect 4 pairs with highest similarity were kept as probably related.
we chose a two-step procedure: (1) A similarity score for each pair of synonymous words from the same dataset is inferred using supervised learning, and (2) these inferred similarities are used as input for unsupervised clustering.