@inproceedings{fae070defe364a44aaaab188ee43a357,
title = "Chinese and Korean cross-lingual issue news detection based on translation knowledge of Wikipedia",
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.",
keywords = "Cross-Lingual link discovery, Issue news detection, Wikipedia knowledge",
author = "Shengnan Zhao and Bayar Tsolmon and Lee, \{Kyung Soon\} and Lee, \{Young Seok\}",
year = "2014",
doi = "10.1007/978-981-4585-18-7\_40",
language = "English",
isbn = "9789814585170",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "353--360",
booktitle = "Proceedings of the First International Conference on Advanced Data and Information Engineering, DaEng 2013",
note = "1st International Conference on Advanced Data and Information Engineering, DaEng 2013 ; Conference date: 16-12-2013 Through 18-12-2013",
}