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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 7180 of 247 papers

TitleStatusHype
Bag Reference Vector for Multi-instance Learning0
BabelDomains: Large-Scale Domain Labeling of Lexical Resources0
A Novel Term_Class Relevance Measure for Text Categorization0
A Visual Quality Index for Fuzzy C-Means0
Automatic Keyword Extraction on Twitter0
A Novel Feature Selection and Extraction Technique for Classification0
A Joint Segmentation and Classification Framework for Sentiment Analysis0
Automatic Keyphrase Extraction: A Survey of the State of the Art0
Automatic Generation of Language-Independent Features for Cross-Lingual Classification0
Annotation Artifacts in Natural Language Inference Data0
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