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Text Categorization

Text Categorization is the task of automatically assigning pre-defined categories to documents written in natural languages. Several types of Text Categorization have been studied, each of which deals with different types of documents and categories, such as topic categorization to detect discussed topics (e.g., sports, politics), spam detection, and sentiment classification to determine the sentiment typically in product or movie reviews.

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

Papers

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Showing 1–25 of 247 papers

TitleStatusHype
Quantum Recurrent Neural Networks for Sequential LearningCode1
NatCat: Weakly Supervised Text Classification with Naturally Annotated ResourcesCode1
Latent Dirichlet AllocationCode1
Improving Document Classification with Multi-Sense EmbeddingsCode1
A comparison of latent semantic analysis and correspondence analysis of document-term matrices—0
A Comparative Study of Pretrained Language Models on Thai Social Text Categorization—0
A Proposal of Automatic Error Correction in Text—0
A Joint Probabilistic Classification Model of Relevant and Irrelevant Sentences in Mathematical Word Problems—0
Active Learning with Rationales for Text Classification—0
A Joint Segmentation and Classification Framework for Sentiment Analysis—0
A Machine Learning Framework for Authorship Identification From Texts—0
A Machine Learning Method to Distinguish Machine Translation from Human Translation—0
A Method of Accounting Bigrams in Topic Models—0
A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing—0
A Hidden Variables Approach to Multilabel Logistic Regression—0
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia—0
An approach based on Combination of Features for automatic news retrieval—0
A New Feature Selection Technique Combined with ELM Feature Space for Text Classification—0
An Examination of Regret in Bullying Tweets—0
Annotation Artifacts in Natural Language Inference Data—0
A Novel Feature Selection and Extraction Technique for Classification—0
A Novel Term_Class Relevance Measure for Text Categorization—0
An Unsupervised Morphological Criterion for Discriminating Similar Languages—0
A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization—0
Analysis of opinionated text for opinion mining—0
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