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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 6170 of 247 papers

TitleStatusHype
ColLex.en: Automatically Generating and Evaluating a Full-form Lexicon for English0
Complex Decomposition of the Negative Distance kernel0
Compressive Feature Learning0
Compression-Based Regularization with an Application to Multi-Task Learning0
A Study of Association Measures and their Combination for Arabic MWT Extraction0
Computing Word Classes Using Spectral Clustering0
Concreteness and Subjectivity as Dimensions of Lexical Meaning0
Consistent Text Categorization using Data Augmentation in e-Commerce0
An approach based on Combination of Features for automatic news retrieval0
Analysis of opinionated text for opinion mining0
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