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- W2114032676 abstract "Cross-lingual issue news and analyzing the news content is an important and challenging task. The core of the cross-lingual research is the process of translation. In this paper, we focus on extracting cross-lingual issue news from the Twitter data of Chinese and Korean. We propose translation knowledge method for Wikipedia concepts as well as the Chinese and Korean cross-lingual inter-Wikipedia link relations. The relevance relations are extracted from the category and the page title of Wikipedia. The evaluation achieved a performance of 83 % in average precision in the top 10 extracted issue news. The result indicates that our method is an effective for cross-lingual issue news detection." @default.
- W2114032676 created "2016-06-24" @default.
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- W2114032676 date "2013-12-15" @default.
- W2114032676 modified "2023-09-27" @default.
- W2114032676 title "Chinese and Korean Cross-Lingual Issue News Detection based on Translation Knowledge of Wikipedia" @default.
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- W2114032676 doi "https://doi.org/10.1007/978-981-4585-18-7_40" @default.
- W2114032676 hasPublicationYear "2013" @default.
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