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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 226–247 of 247 papers

TitleStatusHype
Feature Selection Based on Term Frequency and T-Test for Text Categorization—0
Semantic Similarity Computation for Abstract and Concrete Nouns Using Network-based Distributional Semantic Models—0
DeepPurple: Estimating Sentence Semantic Similarity using N-gram Regression Models and Web Snippets—0
Towards Building a Multilingual Semantic Network: Identifying Interlingual Links in Wikipedia—0
State-of-the-Art Kernels for Natural Language Processing—0
Graph-based Semi-Supervised Learning Algorithms for NLP—0
langid.py: An Off-the-shelf Language Identification Tool—0
Modeling Topic Dependencies in Hierarchical Text Categorization—0
Baselines and Bigrams: Simple, Good Sentiment and Topic Classification—0
Effect of small sample size on text categorization with support vector machines—0
Improving K-Nearest Neighbor Efficacy for Farsi Text Classification—0
A good space: Lexical predictors in word space evaluation—0
French and German Corpora for Audience-based Text Type Classification—0
Is it Useful to Support Users with Lexical Resources? A User Study.—0
Irregularity Detection in Categorized Document Corpora—0
SemSim: Resources for Normalized Semantic Similarity Computation Using Lexical Networks—0
Inverse-Category-Frequency based supervised term weighting scheme for text categorizationCode0
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization—0
Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization—0
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scalesCode0
Latent Dirichlet AllocationCode1
A Sequential Algorithm for Training Text ClassifiersCode0
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