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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 2526–2550 of 4002 papers

TitleStatusHype
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs—0
Reducing Gender Bias in Abusive Language Detection—0
The Influence of Down-Sampling Strategies on SVD Word Embedding Stability—0
SeVeN: Augmenting Word Embeddings with Unsupervised Relation VectorsCode0
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach—0
Syntree2Vec - An algorithm to augment syntactic hierarchy into word embeddings—0
Embedding Grammars—0
Angular-Based Word Meta-Embedding Learning—0
Unsupervised Keyphrase Extraction from Scientific PublicationsCode0
Learning to Represent Bilingual DictionariesCode0
Building a Kannada POS Tagger Using Machine Learning and Neural Network ModelsCode0
Word-Level Loss Extensions for Neural Temporal Relation ClassificationCode0
Instantiation—0
Using Word Embeddings for Unsupervised Acronym Disambiguation—0
Model-Free Context-Aware Word Composition—0
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena—0
A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction—0
AnlamVer: Semantic Model Evaluation Dataset for Turkish - Word Similarity and RelatednessCode0
Learning to Generate Word Representations using Subword Information—0
Modeling with Recurrent Neural Networks for Open Vocabulary Slots—0
Toward Better Loanword Identification in Uyghur Using Cross-lingual Word Embeddings—0
Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological TagsCode0
What's in Your Embedding, And How It Predicts Task Performance—0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activationsCode0
Towards a unified framework for bilingual terminology extraction of single-word and multi-word termsCode0
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