قارن الطرق

	TextCNN	شبكة عصبية متكررة ثنائية الاتجاه
المجال	التعلم العميق	التعلم العميق
العائلة	Machine learning	Machine learning
سنة النشأة	2014	1997
صاحب الطريقة	Kim, Y.	Schuster, M. & Paliwal, K.K.
النوع	Convolutional neural network (deep learning)	Recurrent neural network (sequence model)
المصدر التأسيسي	Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. EMNLP.	Schuster, M. & Paliwal, K.K. (1997). Bidirectional Recurrent Neural Networks. IEEE Transactions on Signal Processing, 45(11), 2673–2681.
الأسماء البديلة	CNN — Metin Sınıflandırma (TextCNN), convolutional neural network for sentence classification, sentence-level CNN, TextCNN	Çift Yönlü RNN / BiLSTM / BiGRU, bidirectional recurrent neural network, BiLSTM, BiGRU
ذات صلة	5	5
الملخص	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.	A Bidirectional RNN, introduced by Schuster and Paliwal in 1997, processes a sequence in both forward and backward directions so that every position has access to its full surrounding context. With LSTM or GRU cells (BiLSTM/BiGRU) it is the standard approach for named-entity recognition, sequence labelling, and speech recognition.