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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 2126–2150 of 4002 papers

TitleStatusHype
Enhancing Automatic Wordnet Construction Using Word Embeddings—0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
Enhancing Clinical Concept Extraction with Contextual Embeddings—0
Enhancing General Sentiment Lexicons for Domain-Specific Use—0
Enhancing Interpretability using Human Similarity Judgements to Prune Word Embeddings—0
Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources—0
Enhancing Out-Of-Domain Utterance Detection with Data Augmentation Based on Word Embeddings—0
Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition—0
Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization—0
Enhancing the Inside-Outside Recursive Neural Network Reranker for Dependency Parsing—0
Enhancing Topic Extraction in Recommender Systems with Entropy Regularization—0
Enhancing Topic Modeling for Short Texts with Auxiliary Word Embeddings—0
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations—0
Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts—0
Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts—0
Enriching Phrase Tables for Statistical Machine Translation Using Mixed Embeddings—0
Enriching Word Embeddings with Domain Knowledge for Readability Assessment—0
Ensemble Methods to Distinguish Mainland and Taiwan Chinese—0
Ensemble Romanian Dependency Parsing with Neural Networks—0
Entity-Aware Dependency-Based Deep Graph Attention Network for Comparative Preference Classification—0
Entity-Centric Contextual Affective Analysis—0
Entity Linking for Queries by Searching Wikipedia Sentences—0
Entropy-Based Subword Mining with an Application to Word Embeddings—0
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques—0
Equipping Educational Applications with Domain Knowledge—0
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