We describe an approach to improve the bilingual cooccurrence dictionary that is used for word alignment, and evaluate the improved dictionary using a version of the Competitive Linking algorithm. We demonstrate a problem faced by the Competitive Linking algorithm and present an approach to ameliorate it. In particular, we rebuild the bilingual dictionary by clustering similar words in a language and assigning them a higher cooccurrence score with a given word in the other language than each single word would have otherwise. Experimental results show a significant improvement in precision and recall for word alignment when the improved dicitonary.
