HieNN-DWE: A hierarchical neural network with dynamic word embeddings for document level sentiment classification

Author:

Liu Fagui,Zheng Lailei,Zheng Jingzhong

Funder

Engineering and Technology Research Center of Guangdong Province for Logistics Supply Chain and Internet of Things

Key Laboratory of Cloud Computing for Super-integration Cloud Computing in Guangdong Province

Engineering and Technology Research Center of Guangdong Province for Big Data Intelligent Processing

Industrial Development Fund Project of Guangzhou

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference49 articles.

1. Cold-start aware user and product attention for sentiment classification;Amplayo,2018

2. Enriching word vectors with subword information;Bojanowski;Trans. Assoc. Comput. Linguist.,2017

3. K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, Y. Bengio, Learning phrase representations using rnn encoder-decoder for statistical machine translation, 2014. arXiv preprint arXiv:1406.1078.

4. Using sentiwordnet for multilingual sentiment analysis;Denecke,2008

5. Naive bayes for text classification with unbalanced classes;Frank,2006

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