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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 3151–3175 of 4002 papers

TitleStatusHype
A Survey Of Cross-lingual Word Embedding Models—0
A Survey on Automatically-Constructed WordNets and their Evaluation: Lexical and Word Embedding-based Approaches—0
A Survey On Neural Word Embeddings—0
A Survey on Word Meta-Embedding Learning—0
A Syllable-based Technique for Word Embeddings of Korean Words—0
Asymmetric Proxy Loss for Multi-View Acoustic Word Embeddings—0
A System for Multilingual Dependency Parsing based on Bidirectional LSTM Feature Representations—0
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification—0
Atalaya at TASS 2019: Data Augmentation and Robust Embeddings for Sentiment Analysis—0
A Topical Approach to Capturing Customer Insight In Social Media—0
A Transparent Framework for Evaluating Unintended Demographic Bias in Word Embeddings—0
A Trie-Structured Bayesian Model for Unsupervised Morphological Segmentation—0
ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks—0
Attending Sentences to detect Satirical Fake News—0
Attending to Characters in Neural Sequence Labeling Models—0
Attention-based model for predicting question relatedness on Stack Overflow—0
Attention-based Semantic Priming for Slot-filling—0
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings—0
Attention improves concentration when learning node embeddings—0
Attention Modeling for Targeted Sentiment—0
attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines—0
A Twitter Corpus and Benchmark Resources for German Sentiment Analysis—0
A Two-Stage Approach for Computing Associative Responses to a Set of Stimulus Words—0
A Typedriven Vector Semantics for Ellipsis with Anaphora using Lambek Calculus with Limited Contraction—0
AUEB-ABSA at SemEval-2016 Task 5: Ensembles of Classifiers and Embeddings for Aspect Based Sentiment Analysis—0
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