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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 171180 of 247 papers

TitleStatusHype
Active Learning with Rationales for Text Classification0
Digital Leafleting: Extracting Structured Data from Multimedia Online Flyers0
Fast Sampling for Bayesian Max-Margin Models0
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding0
Arabic Text Categorization Algorithm using Vector Evaluation Method0
A Novel Feature Selection and Extraction Technique for Classification0
Machine-guided Solution to Mathematical Word Problems0
A Joint Probabilistic Classification Model of Relevant and Irrelevant Sentences in Mathematical Word Problems0
Supervised learning Methods for Bangla Web Document Categorization0
Tunisian dialect Wordnet creation and enrichment using web resources and other Wordnets0
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