Deep CNN-LSTM with combined kernels from multiple branches for IMDb review sentiment analysis
Explore this paper's citation graph
- Type
- article
- Published
- 2017-10-01
- Cited by
- 160
- References
- 25
- OpenAlex
- https://openalex.org/W2783819197
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:23315911
Keywords
Computer science, Overfitting, Sentiment analysis, Artificial intelligence, Convolutional neural network
References
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Convolutional Neural Networks for Sentence Classification
- Character-Aware Neural Language Models
- Techniques and applications for sentiment analysis
- A neural network based approach for sentiment classification in the blogosphere
- Long Short-Term Memory
- Going deeper with convolutions
- Gradient-based learning applied to document recognition
- Learning Word Vectors for Sentiment Analysis
- Machine learning in automated text categorization
- Distributed Representations of Words and Phrases and their Compositionality
- Thumbs up? Sentiment Classification using Machine Learning Techniques
- UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification
- Character-level Convolutional Networks for Text Classification
- An effective model for aspect based opinion mining for social reviews
- Recurrent Convolutional Neural Networks for Text Classification
- Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
- Classification of sentiment reviews using n-gram machine learning approach
- Enriching Word Vectors with Subword Information
- Anomaly Detection in Video Using Predictive Convolutional Long Short-Term Memory Networks
Cited by
- Mobile Personalized Service Recommender Model Based on Sentiment Analysis and Privacy Concern
- Sentiment classification based on deep learning
- A sentiment information Collector-Extractor architecture based neural network for sentiment analysis
- Detecting Signs of Dementia Using Word Vector Representations
- Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization With Medical Applications
- Learning Representations of Natural Language Texts with Generative Adversarial Networks at Document, Sentence, and Aspect Level
- Sentiment analysis via semi-supervised learning: a model based on dynamic threshold and multi-classifiers
- Novel Deep Learning Model with CNN and Bi-Directional LSTM for Improved Stock Market Index Prediction
- Detecting early signs of dementia in conversation
- Sentiment Classification of Reviews Based on BiGRU Neural Network and Fine-grained Attention
- Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
- A CNN-BiLSTM Model for Document-Level Sentiment Analysis
- Lexicon-Enhanced Attention Network Based on Text Representation for Sentiment Classification
- Word Representation Learning Based on Bidirectional GRUs With Drop Loss for Sentiment Classification
- Knowledge Transfer for Rotary Machine Fault Diagnosis
- Detection of Offensive YouTube Comments, a Performance Comparison of Deep Learning Approaches
- Sentiment Analysis of Transjakarta Based on Twitter using Convolutional Neural Network
- Sentiment Analysis Using Residual Learning with Simplified CNN Extractor
- An enhanced approach for movie review analysis using deep learning techniques
- Sequential Multi-Kernel Convolutional Recurrent Network for Sentiment Classification
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