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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 451–475 of 4002 papers

TitleStatusHype
Attention improves concentration when learning node embeddings—0
Attention Modeling for Targeted Sentiment—0
Analyzing Semantic Change in Japanese Loanwords—0
A Domain Adaptation Regularization for Denoising Autoencoders—0
attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines—0
A Twitter Corpus and Benchmark Resources for German Sentiment Analysis—0
A Two-Stage Approach for Computing Associative Responses to a Set of Stimulus Words—0
A Typedriven Vector Semantics for Ellipsis with Anaphora using Lambek Calculus with Limited Contraction—0
AUEB-ABSA at SemEval-2016 Task 5: Ensembles of Classifiers and Embeddings for Aspect Based Sentiment Analysis—0
aueb.twitter.sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis—0
Analyzing the Representational Geometry of Acoustic Word Embeddings—0
Augmenting NLP models using Latent Feature Interpolations—0
Advancing Fake News Detection: Hybrid DeepLearning with FastText and Explainable AI—0
Augmenting Small Data to Classify Contextualized Dialogue Acts for Exploratory Visualization—0
A comparative study of word embeddings and other features for lexical complexity detection in French—0
Author Profiling from Facebook Corpora—0
Analyzing Word Embedding Through Structural Equation Modeling—0
Autoencoding Improves Pre-trained Word Embeddings—0
AutoExtend: Combining Word Embeddings with Semantic Resources—0
AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes—0
Automated Detection of Adverse Drug Reactions in the Biomedical Literature Using Convolutional Neural Networks and Biomedical Word Embeddings—0
An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks—0
Automated Discovery of Mathematical Definitions in Text—0
Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks—0
BERT-Based Neural Collaborative Filtering and Fixed-Length Contiguous Tokens Explanation—0
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