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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 151160 of 247 papers

TitleStatusHype
Improving Large-Scale k-Nearest Neighbor Text Categorization with Label Autoencoders0
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification0
INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis0
Interactive Tools and Tasks for the Hebrew Bible0
Irregularity Detection in Categorized Document Corpora0
Is it Useful to Support Users with Lexical Resources? A User Study.0
JaTeCS an open-source JAva TExt Categorization System0
KeLP: a Kernel-based Learning Platform for Natural Language Processing0
langid.py: An Off-the-shelf Language Identification Tool0
Large-Scale Categorization of Japanese Product Titles Using Neural Attention Models0
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