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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

Showing 201225 of 247 papers

TitleStatusHype
SentiHeros at SemEval-2017 Task 5: An application of Sentiment Analysis on Financial Tweets0
SenTube: A Corpus for Sentiment Analysis on YouTube Social Media0
Sequence-to-Set Semantic Tagging: End-to-End Multi-label Prediction using Neural Attention for Complex Query Reformulation and Automated Text Categorization0
Sequence-to-Set Semantic Tagging for Complex Query Reformulation and Automated Text Categorization in Biomedical IR using Self-Attention0
Sequential Learning of Convolutional Features for Effective Text Classification0
Shortest-Path Graph Kernels for Document Similarity0
SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing0
Authorship Attribution Using Text DistortionCode0
Authorship Attribution Using the Chaos Game RepresentationCode0
Learning Graph Pooling and Hybrid Convolutional Operations for Text RepresentationsCode0
Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive StudyCode0
Rep the Set: Neural Networks for Learning Set RepresentationsCode0
A Model Ensemble Approach with LLM for Chinese Text ClassificationCode0
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text CategorizationCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
Revisiting neural relation classification in clinical notes with external informationCode0
Neural Discourse Structure for Text CategorizationCode0
Very Large Language Model as a Unified Methodology of Text MiningCode0
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical ApplicationsCode0
Improving Arabic Text Categorization Using Transformer Training DiversificationCode0
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scalesCode0
Discriminating between Similar Languages using Weighted Subword FeaturesCode0
A Sequential Algorithm for Training Text ClassifiersCode0
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment AnalysisCode0
Document Informed Neural Autoregressive Topic ModelsCode0
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