摘要
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.
基金
The Major Technologies R&D Special Program of Anhui,China(Grant No.16030901060)
The National Natural Science Foundation of China(Grant No.61502010)
The Natural Science Foundation of Anhui Province(Grant No.1608085QF146)
The Natural Science Foundation of China(Grant No.61806004).