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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 26–50 of 247 papers

TitleStatusHype
Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks—0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data SetCode0
Improving Arabic Text Categorization Using Transformer Training DiversificationCode0
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing—0
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification—0
NatCat: Weakly Supervised Text Classification with Naturally Annotated ResourcesCode1
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based ApproachCode0
Deep learning models for representing out-of-vocabulary words—0
Sequence-to-Set Semantic Tagging for Complex Query Reformulation and Automated Text Categorization in Biomedical IR using Self-Attention—0
Improve Document Embedding for Text Categorization Through Deep Siamese Neural Network—0
Text Categorization for Conflict Event Annotation—0
An approach based on Combination of Features for automatic news retrieval—0
SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text ClassificationCode0
A Machine Learning Framework for Authorship Identification From Texts—0
PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AICode0
A Hidden Variables Approach to Multilabel Logistic Regression—0
A Comparative Study of Pretrained Language Models on Thai Social Text Categorization—0
Improving Document Classification with Multi-Sense EmbeddingsCode1
t-SS3: a text classifier with dynamic n-grams for early risk detection over text streamsCode0
Sequence-to-Set Semantic Tagging: End-to-End Multi-label Prediction using Neural Attention for Complex Query Reformulation and Automated Text Categorization—0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis—0
Ensemble Quantile ClassifierCode0
Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensorflow and Comparison of Performance for Various Hidden Layers—0
Sequential Learning of Convolutional Features for Effective Text Classification—0
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