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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 3951–3975 of 4002 papers

TitleStatusHype
Feature Embedding for Dependency Parsing—0
Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources—0
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts—0
A Probabilistic Model for Learning Multi-Prototype Word Embeddings—0
Co-learning of Word Representations and Morpheme Representations—0
A Two-Stage Approach for Computing Associative Responses to a Set of Stimulus Words—0
Exploring the use of word embeddings and random walks on Wikipedia for the CogAlex shared task—0
Predicting sense convergence with distributional semantics: an application to the CogaLex 2014 shared task—0
SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity—0
UniPi: Recognition of Mentions of Disorders in Clinical Text—0
Blinov: Distributed Representations of Words for Aspect-Based Sentiment Analysis at SemEval 2014—0
Substitute Based SCODE Word Embeddings in Supervised NLP TasksCode0
WordRep: A Benchmark for Research on Learning Word Representations—0
KNET: A General Framework for Learning Word Embedding using Morphological Knowledge—0
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 Representations—0
Linguistic Regularities in Sparse and Explicit Word Representations—0
Learning Semantic Hierarchies via Word Embeddings—0
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 process—0
Bilingually-constrained Phrase Embeddings for Machine Translation—0
Dependency-Based Word Embeddings—0
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction—0
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