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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 2401–2450 of 4002 papers

TitleStatusHype
Interpreting Word Embeddings with Eigenvector AnalysisCode0
Proactive Security: Embedded AI Solution for Violent and Abusive Speech Recognition—0
Learned in Speech Recognition: Contextual Acoustic Word Embeddings—0
Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings—0
pioNER: Datasets and Baselines for Armenian Named Entity RecognitionCode0
Analysis of Railway Accidents' Narratives Using Deep LearningCode0
Subword Semantic Hashing for Intent Classification on Small DatasetsCode0
TNE: A Latent Model for Representation Learning on Networks—0
Skip-Thought GAN: Generating Text through Adversarial Training using Skip-Thought Vectors—0
Poincaré GloVe: Hyperbolic Word EmbeddingsCode0
A Multimodal Approach towards Emotion Recognition of Music using Audio and Lyrical Content—0
Is there Gender bias and stereotype in Portuguese Word Embeddings?—0
textTOvec: Deep Contextualized Neural Autoregressive Topic Models of Language with Distributed Compositional PriorCode0
End-to-End Text Classification via Image-based Embedding using Character-level NetworksCode0
Word Embeddings from Large-Scale Greek Web Content—0
Text-based Sentiment Analysis and Music Emotion Recognition—0
Neural Networks for Cross-lingual Negation Scope Detection—0
Italian Event Detection Goes Deep LearningCode0
A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation—0
A Comparative Study of Neural Network Models for Sentence Classification—0
Shot Or Not: Comparison of NLP Approaches for Vaccination Behaviour Detection—0
Language Independent Sentiment Analysis with Sentiment-Specific Word Embeddings—0
DFKI-MLT System Description for the WMT18 Automatic Post-editing Task—0
Classification of Medication-Related Tweets Using Stacked Bidirectional LSTMs with Context-Aware AttentionCode0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
A Framework for Understanding the Role of Morphology in Universal Dependency Parsing—0
Unsupervised Bilingual Lexicon Induction via Latent Variable Models—0
CEA LIST: Processing Low-Resource Languages for CoNLL 2018Code0
Self-Governing Neural Networks for On-Device Short Text ClassificationCode0
Joint Learning for Targeted Sentiment Analysis—0
Learning Representations for Detecting Abusive Language—0
IRISA at SMM4H 2018: Neural Network and Bagging for Tweet Classification—0
CARER: Contextualized Affect Representations for Emotion RecognitionCode0
Unsupervised Parallel Sentence Extraction from Comparable Corpora—0
Self-training improves Recurrent Neural Networks performance for Temporal Relation Extraction—0
Resources to Examine the Quality of Word Embedding Models Trained on n-Gram Data—0
Learning Text Representations for 500K Classification Tasks on Named Entity DisambiguationCode0
Learning Unsupervised Word Translations Without Adversaries—0
InferLite: Simple Universal Sentence Representations from Natural Language Inference Data—0
In-domain Context-aware Token Embeddings Improve Biomedical Named Entity Recognition—0
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings—0
Refining Pretrained Word Embeddings Using Layer-wise Relevance Propagation—0
Word Embeddings for Code-Mixed Language Processing—0
A Morphology-Based Representation Model for LSTM-Based Dependency Parsing of Agglutinative LanguagesCode0
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research—0
Bringing Order to Neural Word Embeddings with Embeddings Augmented by Random Permutations (EARP)—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
Improved Dependency Parsing using Implicit Word Connections Learned from Unlabeled Data—0
Linking News Sentiment to Microblogs: A Distributional Semantics Approach to Enhance Microblog Sentiment Classification—0
Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings—0
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