Bi-LSTM model to increase accuracy in text classification: Combining Word2vec CNN and attention mechanism
There is a need to extract meaningful information from big data, classify it into different
categories, and predict end-user behavior or emotions. Large amounts of data are …
categories, and predict end-user behavior or emotions. Large amounts of data are …
Getting personal: A deep learning artifact for text-based measurement of personality
Analysts, managers, and policymakers are interested in predictive analytics capable of
offering better foresight. It is generally accepted that in forecasting scenarios involving …
offering better foresight. It is generally accepted that in forecasting scenarios involving …
[HTML][HTML] Automatic classification of cancer pathology reports: a systematic review
Pathology reports primarily consist of unstructured free text and thus the clinical information
contained in the reports is not trivial to access or query. Multiple natural language …
contained in the reports is not trivial to access or query. Multiple natural language …
A hybrid bidirectional recurrent convolutional neural network attention-based model for text classification
J Zheng, L Zheng - IEEE Access, 2019 - ieeexplore.ieee.org
The text classification task is an important application in natural language processing. At
present, deep learning models, such as convolutional neural network and recurrent neural …
present, deep learning models, such as convolutional neural network and recurrent neural …
Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types
In the last decade, the widespread adoption of electronic health record documentation has
created huge opportunities for information mining. Natural language processing (NLP) …
created huge opportunities for information mining. Natural language processing (NLP) …
[PDF][PDF] Review of Text Classification Methods on Deep Learning.
H Wu, Y Liu, J Wang - Computers, Materials & Continua, 2020 - pdfs.semanticscholar.org
Text classification has always been an increasingly crucial topic in natural language
processing. Traditional text classification methods based on machine learning have many …
processing. Traditional text classification methods based on machine learning have many …
Convolutional multi-head self-attention on memory for aspect sentiment classification
Y Zhang, B Xu, T Zhao - IEEE/CAA Journal of Automatica …, 2020 - ieeexplore.ieee.org
This paper presents a method for aspect based sentiment classification tasks, named
convolutional multi-head self-attention memory network (CMA-MemNet). This is an improved …
convolutional multi-head self-attention memory network (CMA-MemNet). This is an improved …
Hierarchical BERT with an adaptive fine-tuning strategy for document classification
Pretrained language models (PLMs) have achieved impressive results and have become
vital tools for various natural language processing (NLP) tasks. However, there is a limitation …
vital tools for various natural language processing (NLP) tasks. However, there is a limitation …
Integration of fuzzy logic and a convolutional neural network in three-way decision-making
With the increase in web usage, opinion mining has become a new trend in analysing
opinions. Nevertheless, opinion mining still faces huge challenges, such as uncertainty in …
opinions. Nevertheless, opinion mining still faces huge challenges, such as uncertainty in …
Deep sentiment analysis: a case study on stemmed Turkish twitter data
Sentiment analysis using stemmed Twitter data from various languages is an emerging
research topic. In this paper, we address three data augmentation techniques namely Shift …
research topic. In this paper, we address three data augmentation techniques namely Shift …