|
Dòng
|
Nội dung
|
|
1
|
A two-channel model for representation learning in vietnamese sentiment classification problem / Nguyen Hoang Quan, Ly Vu, Nguyen Quang Uy // Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics . - 2020. - tr. 13-31. - ISSN: 1813-9663
Ký hiệu phân loại (DDC): 005.13
Sentiment classification ISC) aims to determine whether a document. conveys a positiveor negative opinion. Due to the rapid development of the digital world. SC hm, rwmme an impor-tant research topic that affects to many aspects of our life. In SC hast-d on maritim- Earning. The representation of the document strongly influences on its accuracy. Embedding 35E; swam techniques, techniques. are proved to be beneficial techniques to the SC problem. Howeve is often not. enough to represent the semantic of Vietnamese (1062235 due tothe complexity of semantics and syntactic structure. In this paper. we propose a new:sematiun learning model called a two-channel vector to learn a higher-level feature of a (locum-er: for SC. Our model uses two neural networks to learn both the semantic feature and the feature. The semantic feature is learnt using W'ord and the syntactic feature is learnt tho-.3; Parts of Speech tag (POS). Two features are then combined and input to a Softmax functic-r. 1.51 med-2:3 the final classification.
Số bản sách:
(0)
Tài liệu số:
(1)
|
|
2
|
|
|
|
|
|