Method evidence record
TextCNN
TextCNN is a convolutional neural network for text classification, introduced by Yoon Kim in 2014, that applies parallel convolution filters of different window sizes over word embeddings to capture local n-gram patterns. It is fast and effective for sentiment analysis and topic classification.
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Convolutional Neural Network for Text Classification (TextCNN)
Taxonomic method record · ml-model / deep-learning
- Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. EMNLP. · DOI 10.3115/v1/D14-1181
- Zhang, Y. & Wallace, B. (2015). A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification. arXiv:1510.03820. · URL
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