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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 3426–3450 of 4002 papers

TitleStatusHype
Deceptive Opinion Spam Detection Using Neural Network—0
Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network—0
A Distribution-based Model to Learn Bilingual Word Embeddings—0
Extending WordNet with Fine-Grained Collocational Information via Supervised Distributional Learning—0
Improving Word Alignment of Rare Words with Word Embeddings—0
Word Embeddings and Convolutional Neural Network for Arabic Sentiment ClassificationCode0
Machine Translation Evaluation for Arabic using Morphologically-enriched Embeddings—0
Knowledge-Driven Event Embedding for Stock Prediction—0
Bad Company---Neighborhoods in Neural Embedding Spaces Considered HarmfulCode0
A Deep Fusion Model for Domain Adaptation in Phrase-based MT—0
Weighted Neural Bag-of-n-grams Model: New Baselines for Text ClassificationCode0
CharNER: Character-Level Named Entity RecognitionCode0
Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings—0
Borrow a Little from your Rich Cousin: Using Embeddings and Polarities of English Words for Multilingual Sentiment Classification—0
Facing the most difficult case of Semantic Role Labeling: A collaboration of word embeddings and co-training—0
Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short TextsCode0
Exploring Distributional Representations and Machine Translation for Aspect-based Cross-lingual Sentiment Classification.—0
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs—0
A House United: Bridging the Script and Lexical Barrier between Hindi and Urdu—0
Selective Co-occurrences for Word-Emotion Association—0
Building a Monolingual Parallel Corpus for Text Simplification Using Sentence Similarity Based on Alignment between Word Embeddings—0
On the contribution of word embeddings to temporal relation classification—0
Predictability of Distributional Semantics in Derivational Word Formation—0
D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities—0
Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover's Distance Regularization—0
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