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.
X. Hong, X. Zheng, J. Xia, L. Wei and W. Xue, "Cross-lingual non-ferrous metals related news recognition method based on cnn with a limited bi-lingual dictionary," Computers, Materials & Continua, vol. 58, no.2, pp. 379–389, 2019. https://doi.org/10.32604/cmc.2019.04059
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