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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 191200 of 247 papers

TitleStatusHype
Opinion Mining and Topic Categorization with Novel Term Weighting0
Automatic Keyphrase Extraction: A Survey of the State of the Art0
Bayesian Kernel Methods for Natural Language Processing0
A Composite Kernel Approach for Dialog Topic Tracking with Structured Domain Knowledge from Wikipedia0
Concreteness and Subjectivity as Dimensions of Lexical Meaning0
Linguistic Structured Sparsity in Text Categorization0
VarClass: An Open-source Language Identification Tool for Language Varieties0
Dense Components in the Structure of WordNet0
SenTube: A Corpus for Sentiment Analysis on YouTube Social Media0
Data Mining with Shallow vs. Linguistic Features to Study Diversification of Scientific Registers0
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