@Article{cmc.2019.04059,
AUTHOR = {Xudong  Hong, Xiao  Zheng, Jinyuan  Xia, Linna  Wei, Wei  Xue},
TITLE = {Cross-Lingual Non-Ferrous Metals Related News Recognition Method Based on CNN with A Limited Bi-Lingual Dictionary},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {58},
YEAR = {2019},
NUMBER = {2},
PAGES = {379--389},
URL = {http://www.techscience.com/cmc/v58n2/23015},
ISSN = {1546-2226},
ABSTRACT = {To acquire non-ferrous metals related news from different countries’ internet, we proposed a cross-lingual non-ferrous metals related news recognition method based on CNN with a limited bilingual dictionary. Firstly, considering the lack of related language resources of non-ferrous metals, we use a limited bilingual dictionary and CCA to learn cross-lingual word vector and to represent news in different languages uniformly. Then, to improve the effect of recognition, we use a variant of the CNN to learn recognition features and construct the recognition model. The experimental results show that our proposed method acquires better results.},
DOI = {10.32604/cmc.2019.04059}
}