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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 1626–1650 of 4002 papers

TitleStatusHype
Fusing Vector Space Models for Domain-Specific Applications—0
Fusion approaches for emotion recognition from speech using acoustic and text-based features—0
ScoreGAN: A Fraud Review Detector based on Multi Task Learning of Regulated GAN with Data Augmentation—0
A semi-supervised model for Persian rumor verification based on content information—0
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications—0
Extending and Improving Wordnet via Unsupervised Word Embeddings—0
COIN – an Inexpensive and Strong Baseline for Predicting Out of Vocabulary Word Embeddings—0
Expressivity-aware Music Performance Retrieval using Mid-level Perceptual Features and Emotion Word Embeddings—0
Expressing Objects just like Words: Recurrent Visual Embedding for Image-Text Matching—0
Coherence models in schizophrenia—0
Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives—0
Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification—0
Addressing Biases in the Texts using an End-to-End Pipeline Approach—0
Exponential Family Word Embeddings: An Iterative Approach for Learning Word Vectors—0
Gender Prediction for Chinese Social Media Data—0
Gender Roles from Word Embeddings in a Century of Children’s Books—0
Exponential Family Embeddings—0
CogNLP-Sheffield at CMCL 2021 Shared Task: Blending Cognitively Inspired Features with Transformer-based Language Models for Predicting Eye Tracking Patterns—0
Exploring Word Sense Disambiguation Abilities of Neural Machine Translation Systems (Non-archival Extended Abstract)—0
Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalization—0
CogniVal in Action: An Interface for Customizable Cognitive Word Embedding Evaluation—0
Generating Varied Training Corpora in Runyankore Using a Combined Semantic and Syntactic, Pattern-Grammar-based Approach—0
Exploring word embeddings and phonological similarity for the unsupervised correction of language learner errors—0
Exploring Word Embedding for Drug Name Recognition—0
Exploring Wasserstein Distance across Concept Embeddings for Ontology Matching—0
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