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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 241247 of 247 papers

TitleStatusHype
Text Categorization by Learning Predominant Sense of Words as Auxiliary TaskCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Convex Formulation of Multiple Instance Learning from Positive and Unlabeled BagsCode0
Topic or Style? Exploring the Most Useful Features for Authorship AttributionCode0
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text ClassificationCode0
Leap-LSTM: Enhancing Long Short-Term Memory for Text CategorizationCode0
Multilingual Multi-class Sentiment Classification Using Convolutional Neural NetworksCode0
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