Mining Unseen Name Translations via Detecting Comparable News

P.-S. Cheung, R. Huang, W. Lam, and Y.-Y. Law (PRC)


Text Mining, Multilingual Information Processing, Information Discovery


We develop a framework for mining unseen name trans lations from daily multilingual news stories. Multilingual news articles from various sources are automatically down loaded from the Web. Comparable news in different lan guages are discovered via a gloss translation and an un supervised learning algorithm. Multilingual name cog nates are extracted from each comparable news cluster and matched by a phonetic matching model. Experiments have been conducted on the daily online news and the results show that unseen multilingual name translations can be successfully discovered by our framework.

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