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Academic Paper


Title: Optimization of word alignment clues
Author: Jörg Tiedemann
Email: click here TO access email
Homepage: http://www.let.rug.nl/~tiedeman
Institution: University of Uppsala
Linguistic Field: Text/Corpus Linguistics
Abstract: Statistical, linguistic, and heuristic clues can be used for the alignment of words and multi-word units in parallel texts. This article describes the clue alignment approach and the optimization of its parameters using a genetic algorithm. Word alignment clues can come from various sources such as statistical alignment models, co-occurrence tests, string similarity scores and static dictionaries. A genetic algorithm implementing an evolutionary procedure can be used to optimize the parameters necessary for combining available clues. Experiments on English/Swedish bitext show a significant improvement of about 6% in F-scores compared to the baseline produced by statistical word alignment.

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This article appears IN Natural Language Engineering Vol. 11, Issue 3, which you can READ on Cambridge's site or on LINGUIST .



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