Andrea Mulloni


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2007

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Automatic Prediction of Cognate Orthography Using Support Vector Machines
Andrea Mulloni
Proceedings of the ACL 2007 Student Research Workshop

2006

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Automatic Detection of Orthographics Cues for Cognate Recognition
Andrea Mulloni | Viktor Pekar
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Present-day machine translation technologies crucially depend on the size and quality of lexical resources. Much of recent research in the area has been concerned with methods to build bilingual dictionaries automatically. In this paper we propose a methodology for the automatic detection of cognates between two languages based solely on the orthography of words. From a set of known cognates, the method induces rules capturing regularities of orthographic mutations that a word undergoes when migrating from one language into the other. The rules are then applied as a preprocessing step before measuring the orthographic similarity between putative cognates. As a result, the method allows to achieve an improvement in the F-measure of 11,86% in comparison with detecting cognates based only on the edit distance between them.