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This paper presents a keyword extraction technique that can be used for tracking topics over time. In our work, keywords are a set of significant words in an article that gives high-level description of its contents to readers. Identifying keywords from a large amount of on-line news data is very useful in that it can
keywords of different languages are also revealed. We conducted experiments on a set of Chinese-English bilingual parallel corpora to discover the relationships between documents of these languages.
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