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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 1120 of 247 papers

TitleStatusHype
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural NetworksCode0
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text CategorizationCode0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data SetCode0
A Model Ensemble Approach with LLM for Chinese Text ClassificationCode0
Authorship Attribution Using Text DistortionCode0
A Sequential Algorithm for Training Text ClassifiersCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Beyond original Research Articles Categorization via NLPCode0
Discriminating between Similar Languages using Weighted Subword FeaturesCode0
Authorship Attribution Using the Chaos Game RepresentationCode0
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