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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 131140 of 247 papers

TitleStatusHype
Fast Sampling for Bayesian Max-Margin Models0
Feature Hashing for Language and Dialect Identification0
Feature Selection Based on Term Frequency and T-Test for Text Categorization0
Finding a Character's Voice: Stylome Classification on Literary Characters0
French and German Corpora for Audience-based Text Type Classification0
From high heels to weed attics: a syntactic investigation of chick lit and literature0
From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings0
FSMJ: Feature Selection with Maximum Jensen-Shannon Divergence for Text Categorization0
GPKEX: Genetically Programmed Keyphrase Extraction from Croatian Texts0
Graph-based Semi-Supervised Learning Algorithms for NLP0
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