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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 4150 of 247 papers

TitleStatusHype
Automatic Generation of Language-Independent Features for Cross-Lingual Classification0
Automatic Keyphrase Extraction: A Survey of the State of the Art0
Automatic Keyword Extraction on Twitter0
A Visual Quality Index for Fuzzy C-Means0
BabelDomains: Large-Scale Domain Labeling of Lexical Resources0
Bag Reference Vector for Multi-instance Learning0
Balancing Between Over-Weighting and Under-Weighting in Supervised Term Weighting0
Baselines and Bigrams: Simple, Good Sentiment and Topic Classification0
Bayesian Kernel Methods for Natural Language Processing0
Analysis of opinionated text for opinion mining0
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