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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
Robust Gram EmbeddingsCode0
Effective Greedy Inference for Graph-based Non-Projective Dependency Parsing—0
Learning principled bilingual mappings of word embeddings while preserving monolingual invarianceCode1
Context-Dependent Sense Embedding—0
Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network—0
A Graph Degeneracy-based Approach to Keyword ExtractionCode0
Exploring Semantic Representation in Brain Activity Using Word Embeddings—0
Learning Connective-based Word Representations for Implicit Discourse Relation Identification—0
SimpleScience: Lexical Simplification of Scientific Terminology—0
Learning Sentence Embeddings with Auxiliary Tasks for Cross-Domain Sentiment Classification—0
Multi-Granularity Chinese Word Embedding—0
Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings—0
An Embedding Model for Predicting Roll-Call Votes—0
Improving Twitter Sentiment Classification via Multi-Level Sentiment-Enriched 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
Dialogue Session Segmentation by Embedding-Enhanced TextTiling—0
Compressing Neural Language Models by Sparse Word RepresentationsCode0
Language Models with Pre-Trained (GloVe) Word EmbeddingsCode0
A Dynamic Window Neural Network for CCG Supertagging—0
Neural-based Noise Filtering from Word EmbeddingsCode0
Comparative study of LSA vs Word2vec embeddings in small corpora: a case study in dreams database—0
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