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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 201210 of 247 papers

TitleStatusHype
Data Mining with Shallow vs. Linguistic Features to Study Diversification of Scientific Registers0
Mapping WordNet Domains, WordNet Topics and Wikipedia Categories to Generate Multilingual Domain Specific Resources0
VarClass: An Open-source Language Identification Tool for Language Varieties0
Wikipedia-based Semantic Interpretation for Natural Language Processing0
Creation of Lexical Relations for IndoWordNet0
Compressive Feature Learning0
Automatic Corpora Construction for Text Classification0
The Bregman Variational Dual-Tree Framework0
Text segmentation for Language Identification in Greek Forums0
Towards Basque Oral Poetry Analysis: A Machine Learning Approach0
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