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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 3501–3525 of 4002 papers

TitleStatusHype
Attending to Characters in Neural Sequence Labeling Models—0
A Comparison of Word Embeddings for English and Cross-Lingual Chinese Word Sense Disambiguation—0
Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches—0
Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and DocumentsCode0
Automated Generation of Multilingual Clusters for the Evaluation of Distributed RepresentationsCode0
An Embedding Model for Predicting Roll-Call Votes—0
Improving Twitter Sentiment Classification via Multi-Level Sentiment-Enriched Word Embeddings—0
A Graph Degeneracy-based Approach to Keyword ExtractionCode0
SimpleScience: Lexical Simplification of Scientific Terminology—0
Context-Dependent Sense Embedding—0
Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings—0
Learning Connective-based Word Representations for Implicit Discourse Relation Identification—0
Robust Gram EmbeddingsCode0
Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network—0
Effective Greedy Inference for Graph-based Non-Projective Dependency Parsing—0
Multi-Granularity Chinese Word Embedding—0
Learning Sentence Embeddings with Auxiliary Tasks for Cross-Domain Sentiment Classification—0
Exploring Semantic Representation in Brain Activity Using Word Embeddings—0
Word Embeddings for the Construction DomainCode0
Word Embeddings to Enhance Twitter Gang Member Profile Identification—0
Word Embeddings and Their Use In Sentence Classification Tasks—0
Lexicon Integrated CNN Models with Attention for Sentiment Analysis—0
Bidirectional LSTM-CRF for Clinical Concept ExtractionCode0
Compressing Neural Language Models by Sparse Word RepresentationsCode0
Dialogue Session Segmentation by Embedding-Enhanced TextTiling—0
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