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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
Beyond original Research Articles Categorization via NLPCode0
Structure-Aware Convolutional Neural NetworksCode0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Massively Multilingual Word EmbeddingsCode0
pke: an open source python-based keyphrase extraction toolkitCode0
Text Ranking and Classification using Data CompressionCode0
Ensemble Quantile ClassifierCode0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data SetCode0
Inverse-Category-Frequency based supervised term weighting scheme for text categorizationCode0
PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AICode0
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural NetworksCode0
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based ApproachCode0
SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text ClassificationCode0
t-SS3: a text classifier with dynamic n-grams for early risk detection over text streamsCode0
SeVeN: Augmenting Word Embeddings with Unsupervised Relation VectorsCode0
Text Categorization by Learning Predominant Sense of Words as Auxiliary TaskCode0
An Automated Text Categorization Framework based on Hyperparameter OptimizationCode0
Convex Formulation of Multiple Instance Learning from Positive and Unlabeled BagsCode0
Topic or Style? Exploring the Most Useful Features for Authorship AttributionCode0
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text ClassificationCode0
Leap-LSTM: Enhancing Long Short-Term Memory for Text CategorizationCode0
Multilingual Multi-class Sentiment Classification Using Convolutional Neural NetworksCode0
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