This paper proposes a novel method for lexicon extraction that extracts translation pairs from comparable corpora by using graphbased label propagation. In previous work, it was established that performance drastically decreases when the coverage of a seed lexicon is small. We resolve this problem by utilizing indirect relations with the bilingual seeds together with direct relations, in which each word is represented by a distribution of translated seeds. The seed distributions are propagated over a graph representing relations among words, and translation pairs are extracted by identifying word pairs with a high similarity in the seed distributions. We propose two types of the graphs: a co-occurrence graph, representing co-occurrence relations between words, and a similarity graph, representing context similarities between words. Evaluations using English and Japanese patent comparable corpora show that our proposed graph propagation method outperforms conventional methods. Further, the similarity graph achieved improved performance by clustering synonyms into the same translation.
REF proposes a novel method for lexicon extraction that extracts translation pairs from comparable corpora by using graph-based label propagation.
Bilingual Lexicon Extraction from Comparable Corpora Using Label Propagation
EMNLP
Computer Science