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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

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Showing 26–50 of 247 papers

TitleStatusHype
A Proposal of Automatic Error Correction in Text—0
Arabic Text Categorization Algorithm using Vector Evaluation Method—0
A Semi-supervised Approach for Natural Language Call Routing—0
A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing—0
Aspect and Sentiment Aware Abstractive Review Summarization—0
A good space: Lexical predictors in word space evaluation—0
A Text Classification Application: Poet Detection from Poetry—0
A Study of Association Measures and their Combination for Arabic MWT Extraction—0
An approach based on Combination of Features for automatic news retrieval—0
A Hidden Variables Approach to Multilabel Logistic Regression—0
Auto-clustering Output Layer: Automatic Learning of Latent Annotations in Neural Networks—0
Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers—0
Automatic Categorization of Tagalog Documents Using Support Vector Machines—0
Automatic Classification by Topic Domain for Meta Data Generation, Web Corpus Evaluation, and Corpus Comparison—0
Automatic Corpora Construction for Text Classification—0
Automatic Generation of Language-Independent Features for Cross-Lingual Classification—0
Automatic Keyphrase Extraction: A Survey of the State of the Art—0
Automatic Keyword Extraction on Twitter—0
A Visual Quality Index for Fuzzy C-Means—0
BabelDomains: Large-Scale Domain Labeling of Lexical Resources—0
Bag Reference Vector for Multi-instance Learning—0
Balancing Between Over-Weighting and Under-Weighting in Supervised Term Weighting—0
Baselines and Bigrams: Simple, Good Sentiment and Topic Classification—0
Bayesian Kernel Methods for Natural Language Processing—0
Analysis of opinionated text for opinion mining—0
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