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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
Mapping WordNet Domains, WordNet Topics and Wikipedia Categories to Generate Multilingual Domain Specific Resources0
MaxMin Linear Initialization for Fuzzy C-Means0
Measuring Term Informativeness in Context0
Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks0
Modeling Topic Dependencies in Hierarchical Text Categorization0
Modeling Trolling in Social Media Conversations0
Monitoring Energy Trends through Automatic Information Extraction0
Muli-label Text Categorization with Hidden Components0
Multi-Granular Text Encoding for Self-Explaining Categorization0
Multi-label Text Categorization with Joint Learning Predictions-as-Features Method0
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