  More and more languages in the world are under study nowadays, as a result,
the traditional way of historical linguistics study is facing some challenges.
For example, the linguistic comparative research among languages needs manual
annotation, which becomes more and more impossible with the increasing amount
of language data coming out all around the world. Although it could hardly
replace linguists work, the automatic computational methods have been taken
into consideration and it can help people reduce their workload. One of the
most important work in historical linguistics is word comparison from different
languages and find the cognate words for them, which means people try to figure
out if the two languages are related to each other or not. In this paper, I am
going to use computational method to cluster the languages and use Markov Chain
Monte Carlo (MCMC) method to build the language typology relationship tree
based on the clusters.
