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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

Showing 39514000 of 4002 papers

TitleStatusHype
Feature Embedding for Dependency Parsing0
Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources0
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts0
A Probabilistic Model for Learning Multi-Prototype Word Embeddings0
Co-learning of Word Representations and Morpheme Representations0
A Two-Stage Approach for Computing Associative Responses to a Set of Stimulus Words0
Exploring the use of word embeddings and random walks on Wikipedia for the CogAlex shared task0
Predicting sense convergence with distributional semantics: an application to the CogaLex 2014 shared task0
SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity0
UniPi: Recognition of Mentions of Disorders in Clinical Text0
Blinov: Distributed Representations of Words for Aspect-Based Sentiment Analysis at SemEval 20140
Substitute Based SCODE Word Embeddings in Supervised NLP TasksCode0
WordRep: A Benchmark for Research on Learning Word Representations0
KNET: A General Framework for Learning Word Embedding using Morphological Knowledge0
Event Role Labelling using a Neural Network Model (\'Etiquetage en r\^oles \'ev\'enementiels fond\'e sur l'utilisation d'un mod\`ele neuronal) [in French]0
Deep Neural Network applied to Part-of-Speech Tagging (R\'eseau de neurones profond pour l'\'etiquetage morpho-syntaxique) [in French]0
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations0
Linguistic Regularities in Sparse and Explicit Word Representations0
Learning Semantic Hierarchies via Word Embeddings0
Improving Lexical Embeddings with Semantic KnowledgeCode0
How much do word embeddings encode about syntax?0
POS induction with distributional and morphological information using a distance-dependent Chinese restaurant process0
Bilingually-constrained Phrase Embeddings for Machine Translation0
Dependency-Based Word Embeddings0
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction0
Semantic Frame Identification with Distributed Word Representations0
Community Evaluation and Exchange of Word Vectors at wordvectors.org0
Use of unsupervised word classes for entity recognition: Application to the detection of disorders in clinical reports0
Lexicon Infused Phrase Embeddings for Named Entity Resolution0
Extractive Summarization using Continuous Vector Space Models0
Word Embeddings through Hellinger PCA0
Improving Vector Space Word Representations Using Multilingual Correlation0
word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding methodCode0
Learning Multilingual Word Representations using a Bag-of-Words Autoencoder0
Improved CCG Parsing with Semi-supervised Supertagging0
Word Emdeddings through Hellinger PCA0
Learning word embeddings efficiently with noise-contrastive estimation0
The AI-KU System at the SPMRL 2013 Shared Task : Unsupervised Features for Dependency ParsingCode0
Bilingual Word Embeddings for Phrase-Based Machine Translation0
A Structured Distributional Semantic Model : Integrating Structure with Semantics0
Aggregating Continuous Word Embeddings for Information Retrieval0
Better Word Representations with Recursive Neural Networks for Morphology0
Re-embedding words0
A Structured Distributional Semantic Model for Event Co-reference0
Polyglot: Distributed Word Representations for Multilingual NLP0
Compound Embedding Features for Semi-supervised Learning0
Tagging a Morphologically Complex Language Using an Averaged Perceptron Tagger: The Case of Icelandic0
The Expressive Power of Word Embeddings0
Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding0
Penn: Using Word Similarities to better Estimate Sentence Similarity0
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