SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 247 papers

TitleStatusHype
Learning Non-Linear Functions for Text Classification—0
A New Feature Selection Technique Combined with ELM Feature Space for Text Classification—0
Cross-lingual Dataless Classification for Languages with Small Wikipedia Presence—0
Probabilistic Modeling of Progressive Filtering—0
Regularizing Text Categorization with Clusters of Words—0
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural NetworksCode0
Term-Class-Max-Support (TCMS): A Simple Text Document Categorization Approach Using Term-Class Relevance Measure—0
Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level—0
A Novel Term_Class Relevance Measure for Text Categorization—0
Automatic Classification by Topic Domain for Meta Data Generation, Web Corpus Evaluation, and Corpus Comparison—0
Text2voronoi: An Image-driven Approach to Differential Diagnosis—0
A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization—0
Transductive Adaptation of Black Box Predictions—0
Analysis of opinionated text for opinion mining—0
FSMJ: Feature Selection with Maximum Jensen-Shannon Divergence for Text Categorization—0
DeepStance at SemEval-2016 Task 6: Detecting Stance in Tweets Using Character and Word-Level CNNs—0
Using Linear Classifiers for the Automatic Triage of Posts in the 2016 CLPsych Shared Task—0
UWB at SemEval-2016 Task 7: Novel Method for Automatic Sentiment Intensity Determination—0
SODA:Service Oriented Domain Adaptation Architecture for Microblog Categorization—0
EEF: Exponentially Embedded Families with Class-Specific Features for Classification—0
Improving Bilingual Terminology Extraction from Comparable Corpora via Multiple Word-Space Models—0
Balancing Between Over-Weighting and Under-Weighting in Supervised Term Weighting—0
Interactive Tools and Tasks for the Hebrew Bible—0
Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings—0
Massively Multilingual Word EmbeddingsCode0
Show:102550
← PrevPage 6 of 10Next →

No leaderboard results yet.