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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 121130 of 247 papers

TitleStatusHype
Theoretical Foundations of Forward Feature Selection Methods based on Mutual Information0
Learning Non-Linear Functions for Text Classification0
DISCO: A System Leveraging Semantic Search in Document Review0
An Unsupervised Morphological Criterion for Discriminating Similar Languages0
pke: an open source python-based keyphrase extraction toolkitCode0
A New Feature Selection Technique Combined with ELM Feature Space for Text Classification0
Text Retrieval by Term Co-occurrences in a Query-based Vector Space0
UnibucKernel: An Approach for Arabic Dialect Identification Based on Multiple String Kernels0
Cross-lingual Dataless Classification for Languages with Small Wikipedia Presence0
Probabilistic Modeling of Progressive Filtering0
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