Cognate Discovery and Alignment in Computational Etymology

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http://urn.fi/URN:NBN:fi-fe2017112251391
Title: Cognate Discovery and Alignment in Computational Etymology
Author: Lv, Guowei
Contributor: University of Helsinki, Faculty of Science, Department of Computer Science
Thesis level: master's thesis
Abstract: This master thesis discusses two main tasks of computational etymology. First, finding cognates in multilingual text. Second, finding underlying correspondence rules by aligning cognates. For the first part, I briefly described two categories of methods in identifying cognates: symbol based and phonetic based. For the second part, I described the Etymon project, which I had been working in. The Etymon project uses a probabilistic method and Minimum Description Length principle to align cognate sets. The objective of this project is to build a model which can automatically find as much information in the cognates as possible without linguistic knowledge as well as find genetic relationship between those languages. I also discussed the experiment that I did to explore the uncertainty in the data source.
URI: URN:NBN:fi-fe2017112251391
http://hdl.handle.net/10138/43187
Date: 2014
Discipline: Algorithms and Machine Learning
Algorithms and Machine Learning
Algorithms and Machine Learning


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