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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 101–125 of 247 papers

TitleStatusHype
High-Throughput and Language-Agnostic Entity Disambiguation and Linking on User Generated Data—0
IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis—0
IKM at SemEval-2017 Task 8: Convolutional Neural Networks for stance detection and rumor verification—0
Improve Document Embedding for Text Categorization Through Deep Siamese Neural Network—0
Improving Bilingual Terminology Extraction from Comparable Corpora via Multiple Word-Space Models—0
Improving K-Nearest Neighbor Efficacy for Farsi Text Classification—0
Improving Large-Scale k-Nearest Neighbor Text Categorization with Label Autoencoders—0
Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification—0
INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis—0
Interactive Tools and Tasks for the Hebrew Bible—0
Irregularity Detection in Categorized Document Corpora—0
Is it Useful to Support Users with Lexical Resources? A User Study.—0
JaTeCS an open-source JAva TExt Categorization System—0
KeLP: a Kernel-based Learning Platform for Natural Language Processing—0
langid.py: An Off-the-shelf Language Identification Tool—0
Large-Scale Categorization of Japanese Product Titles Using Neural Attention Models—0
Latent Semantic Matching: Application to Cross-language Text Categorization without Alignment Information—0
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization—0
Learning Non-Linear Functions for Text Classification—0
Learning Timeline Difference for Text Categorization—0
Learning with Inadequate and Incorrect Supervision—0
Linguistic Structured Sparsity in Text Categorization—0
Linguistic Template Extraction for Recognizing Reader-Emotion and Emotional Resonance Writing Assistance—0
Linking, Searching, and Visualizing Entities in Wikipedia—0
Machine-guided Solution to Mathematical Word Problems—0
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