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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 2101–2150 of 4002 papers

TitleStatusHype
EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text—0
EmoNLP at IEST 2018: An Ensemble of Deep Learning Models and Gradient Boosting Regression Tree for Implicit Emotion Prediction in Tweets—0
EmoTech: A Multi-modal Speech Emotion Recognition Using Multi-source Low-level Information with Hybrid Recurrent Network—0
Emotion-Cause Pair Extraction in Customer Reviews—0
Emotion Enriched Retrofitted Word Embeddings—0
EmotionX-Area66: Predicting Emotions in Dialogues using Hierarchical Attention Network with Sequence Labeling—0
Empirical Analysis of Image Caption Generation using Deep Learning—0
Empirical Autopsy of Deep Video Captioning Frameworks—0
Empirical Study of Diachronic Word Embeddings for Scarce Data—0
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction—0
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts—0
Empty Category Detection using Path Features and Distributed Case Frames—0
Enabling Cognitive Intelligence Queries in Relational Databases using Low-dimensional Word Embeddings—0
Enabling Open-World Specification Mining via Unsupervised Learning—0
En-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects—0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Encoding Prior Knowledge with Eigenword Embeddings—0
Encoding Sentiment Information into Word Vectors for Sentiment Analysis—0
End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings—0
ENGLAWI: From Human- to Machine-Readable Wiktionary—0
English-Malay Cross-Lingual Embedding Alignment using Bilingual Lexicon Augmentation—0
English-Malay Word Embeddings Alignment for Cross-lingual Emotion Classification with Hierarchical Attention Network—0
English Resource Semantics—0
English WordNet Random Walk Pseudo-Corpora—0
Enhanced Word Representations for Bridging Anaphora Resolution—0
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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