A Survey of Neural Network Techniques for Feature Extraction from Text
It provides a comprehensive overview for researchers and practitioners in computational linguistics, but it is incremental as it synthesizes existing work without introducing new methods.
This paper surveys neural network techniques for feature extraction from text, summarizing state-of-the-art methods used in language processing, generation, classification, and other computational linguistics tasks.
This paper aims to catalyze the discussions about text feature extraction techniques using neural network architectures. The research questions discussed in the paper focus on the state-of-the-art neural network techniques that have proven to be useful tools for language processing, language generation, text classification and other computational linguistics tasks.