文本分类论文阅读笔记

文章目录

    • CNN系列
      • Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
      • A Convolutional Neural Network for Modelling Sentences
      • Convolutional Neural Networks for Sentence Classification
      • Deep Pyramid Convolutional Neural Networks for Text Categorization
      • Super Characters: A Conversion from Sentiment Classification to Image Classification
    • LSTM系列
      • Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
      • Hierarchical Attention Networks for Document Classification
    • Pre-train
      • Fine-tuned Language Models(FitLaM)
      • Universal Language Model Fine-tuning for Text Classification
    • 其他
      • fastText(Bag of Tricks for Efficient Text Classification)

这篇博客只是个索引, 具体的阅读笔记请点击每篇论文的链接.

CNN系列

Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

阅读笔记

A Convolutional Neural Network for Modelling Sentences

DCNN阅读笔记

Convolutional Neural Networks for Sentence Classification

text-CNN阅读笔记

Deep Pyramid Convolutional Neural Networks for Text Categorization

DPCNN阅读笔记

Super Characters: A Conversion from Sentiment Classification to Image Classification

主要思想:把文字转化成图,然后用图片进行训练。

文本分类论文阅读笔记_第1张图片

LSTM系列

Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification

Att-BLSTM阅读笔记

Hierarchical Attention Networks for Document Classification

HAN阅读笔记

Pre-train

Fine-tuned Language Models(FitLaM)

算是ULMFiT的前身, 基本一样.

Universal Language Model Fine-tuning for Text Classification

ULMFiT阅读笔记

其他

fastText(Bag of Tricks for Efficient Text Classification)

fastText阅读笔记

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