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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 3551–3600 of 4002 papers

TitleStatusHype
Deconstructing and reconstructing word embedding algorithms—0
Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks—0
Deconstructing word embedding algorithms—0
Deconstructing Word Embeddings—0
Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings—0
Deep Bidirectional Transformers for Relation Extraction without Supervision—0
Deep Clustering with Measure Propagation—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing -- A Tale of Two Parsers Revisited—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited—0
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts—0
Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations—0
Deeper Attention to Abusive User Content Moderation—0
DeepHate: Hate Speech Detection via Multi-Faceted Text Representations—0
Deep Learning and Word Embeddings for Tweet Classification for Crisis Response—0
Deep Learning based Topic Analysis on Financial Emerging Event Tweets—0
Deep Learning for Opinion Mining and Topic Classification of Course Reviews—0
Deep Learning for Social Media Health Text Classification—0
Deep learning model for Mongolian Citizens Feedback Analysis using Word Vector Embeddings—0
Deep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter—0
Deep Learning Paradigm with Transformed Monolingual Word Embeddings for Multilingual Sentiment Analysis—0
Deep Learning Techniques for Humor Detection in Hindi-English Code-Mixed Tweets—0
DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning—0
Deep Multilingual Correlation for Improved Word Embeddings—0
Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey—0
Deep Neural Network applied to Part-of-Speech Tagging (R\'eseau de neurones profond pour l'\'etiquetage morpho-syntaxique) [in French]—0
Deep Neural Networks for Query Expansion using Word Embeddings—0
Deep Neural Networks for Syntactic Parsing of Morphologically Rich Languages—0
DeepNL: a Deep Learning NLP pipeline—0
DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets—0
deepSA at SemEval-2017 Task 4: Interpolated Deep Neural Networks for Sentiment Analysis in Twitter—0
Leveraging Deep Graph-Based Text Representation for Sentiment Polarity Applications—0
DeepTC -- An Extension of DKPro Text Classification for Fostering Reproducibility of Deep Learning Experiments—0
DeepXML: Scalable & Accurate Deep Extreme Classification for Matching User Queries to Advertiser Bid Phrases—0
"Definition Modeling: To model definitions." Generating Definitions With Little to No Semantics—0
Delexicalized Word Embeddings for Cross-lingual Dependency Parsing—0
Delta Embedding Learning—0
De-Mixing Sentiment from Code-Mixed Text—0
Demographic Word Embeddings for Racism Detection on Twitter—0
Demonstration of a Literature Based Discovery System based on Ontologies, Semantic Filters and Word Embeddings for the Raynaud Disease-Fish Oil Rediscovery—0
Denoising Word Embeddings by Averaging in a Shared Space—0
Dependency Based Embeddings for Sentence Classification Tasks—0
Dependency-Based Semantic Role Labeling using Convolutional Neural Networks—0
Dependency-Based Word Embeddings—0
Dependency Link Embeddings: Continuous Representations of Syntactic Substructures—0
Dependency Parsing for Urdu: Resources, Conversions and Learning—0
Explainable Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media—0
Derivational Morphological Relations in Word Embeddings—0
Derivational Morphological Relations in Word Embeddings—0
Deriving Contextualised Semantic Features from BERT (and Other Transformer Model) Embeddings—0
Deriving continous grounded meaning representations from referentially structured multimodal contexts—0
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