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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 161170 of 247 papers

TitleStatusHype
Latent Semantic Matching: Application to Cross-language Text Categorization without Alignment Information0
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization0
Learning Non-Linear Functions for Text Classification0
Learning Timeline Difference for Text Categorization0
Learning with Inadequate and Incorrect Supervision0
Linguistic Structured Sparsity in Text Categorization0
Linguistic Template Extraction for Recognizing Reader-Emotion and Emotional Resonance Writing Assistance0
Linking, Searching, and Visualizing Entities in Wikipedia0
Machine-guided Solution to Mathematical Word Problems0
Machine learning approach for text and document mining0
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