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Contrastive learning with text augmentation for text classification
Various contrastive learning models have been successfully applied to representation learning for downstream tasks. The positive samples used in...
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Text Classification
Text classification, also known as text categorization, is a process used in accounting and finance academic research to analyze the language used in...
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Text Classification
Text classification involves assigning labels to text that denote a particular category, for example whether the sentiment expressed in this text is...
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Text length considered adaptive bagging ensemble learning algorithm for text classification
Ensemble learning constructs strong classifiers by training multiple weak classifiers, and is widely used in text classification field. In order to...
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Text Classification
This chapter describes the entire process of text classification based on supervised learning. Each and every step will be explained with the help of...
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Feature-enhanced text-inception model for Chinese long text classification
To solve the problem regarding unbalanced distribution of multi-category Chinese long texts and improve the classification accuracy thereof, a data...
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Text classification framework for short text based on TFIDF-FastText
Text classification is an issue of high priority in text mining, information retrieval that needs to address the problem of capturing the semantic...
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Graph neural networks for text classification: a survey
Text Classification is the most essential and fundamental problem in Natural Language Processing. While numerous recent text classification models...
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Transformer and Graph Convolutional Network for Text Classification
Graph convolutional network (GCN) is an effective tool for feature clustering. However, in the text classification task, the traditional TextGCN (GCN...
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Text classification using embeddings: a survey
Text classification results can be hindered when just the bag-of-words model is used for representing features, because it ignores word order and...
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Federated Freeze BERT for text classification
Pre-trained BERT models have demonstrated exceptional performance in the context of text classification tasks. Certain problem domains necessitate...
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Novel GCN Model Using Dense Connection and Attention Mechanism for Text Classification
Convolutional Neural Network (CNN) or Recurrent Neural Network (RNN) based text classification algorithms currently in use can successfully extract...
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TAE: Topic-aware encoder for large-scale multi-label text classification
Convolutional neural networks, recurrent neural networks, and transformers have excelled in representation learning for large-scale multi-label text...
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A medical text classification approach with ZEN and capsule network
Text classification is an important topic in natural language processing, with the development of social network, many question-and-answer pairs...
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Detecting textual adversarial examples through text modification on text classification systems
In this paper, we propose a method for detecting adversarial examples using a text modification module. The proposed method detects adversarial...
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Filter feature selection methods for text classification: a review
Filter feature selection methods are utilized to select discriminative terms from high-dimensional text data to improve text classification...
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Integrating information by Kullback–Leibler constraint for text classification
Text classification is an important assignment for various text-related downstream assignments, such as fake news detection, sentiment analysis, and...
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Causal representation for few-shot text classification
Few-Shot Text Classification (FSTC) is a fundamental natural language processing problem that aims to classify small amounts of text with high...
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Text Classification System
This chapter is concerned with the text classification system which is implemented with a deep learning algorithm. Text classification as the...
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Research on sensitive text classification detection and classification based on improved artificial neural network
With the rapid development of information technology, a large number of sensitive words have appeared, which has brought great harm to network...
