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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
Compressive Feature Learning—0
Computationally efficient discrimination between language varieties with large feature vectors and regularized classifiers—0
Computing Word Classes Using Spectral Clustering—0
Concreteness and Subjectivity as Dimensions of Lexical Meaning—0
Consistent Text Categorization using Data Augmentation in e-Commerce—0
Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level—0
Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization—0
Creation of Lexical Relations for IndoWordNet—0
Cross-Language Plagiarism Detection Methods—0
Cross-lingual and generic text categorization (Apprentissage d'une classification th\'ematique g\'en\'erique et cross-langue \`a partir des cat\'egories de la Wikip\'edia) [in French]—0
Cross-lingual Dataless Classification for Languages with Small Wikipedia Presence—0
Cross-lingual Synonymy Overlap—0
Data Mining with Shallow vs. Linguistic Features to Study Diversification of Scientific Registers—0
Deep learning models for representing out-of-vocabulary words—0
Deep Learning of Nonnegativity-Constrained Autoencoders for Enhanced Understanding of Data—0
DeepPurple: Estimating Sentence Semantic Similarity using N-gram Regression Models and Web Snippets—0
DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity Estimation—0
DeepStance at SemEval-2016 Task 6: Detecting Stance in Tweets Using Character and Word-Level CNNs—0
Dense Components in the Structure of WordNet—0
Digital Leafleting: Extracting Structured Data from Multimedia Online Flyers—0
DISCO: A System Leveraging Semantic Search in Document Review—0
Discriminative and Consistent Similarities in Instance-Level Multiple Instance Learning—0
Diversifying Neural Conversation Model with Maximal Marginal Relevance—0
ECNUCS: Measuring Short Text Semantic Equivalence Using Multiple Similarity Measurements—0
EEF: Exponentially Embedded Families with Class-Specific Features for Classification—0
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