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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 3001–3025 of 4002 papers

TitleStatusHype
Analyzing Correlations Between Intrinsic and Extrinsic Bias Metrics of Static Word Embeddings With Their Measuring Biases Aligned—0
Analyzing Semantic Change in Japanese Loanwords—0
Analyzing the Framing of 2020 Presidential Candidates in the News—0
Analyzing the Limitations of Cross-lingual Word Embedding Mappings—0
Analyzing the Representational Geometry of Acoustic Word Embeddings—0
Analyzing Word Embedding Through Structural Equation Modeling—0
An Analysis of Deep Contextual Word Embeddings and Neural Architectures for Toponym Mention Detection in Scientific Publications—0
An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks—0
An Analysis of Hierarchical Text Classification Using Word Embeddings—0
An analysis of the user occupational class through Twitter content—0
Anaphora Resolution in Dialogue Systems for South Asian Languages—0
An Artificial Language Evaluation of Distributional Semantic Models—0
An Attentive Fine-Grained Entity Typing Model with Latent Type Representation—0
An Automated Method to Enrich Consumer Health Vocabularies Using GloVe Word Embeddings and An Auxiliary Lexical Resource—0
An Automatic Learning of an Algerian Dialect Lexicon by using Multilingual Word Embeddings—0
Anchor-based Bilingual Word Embeddings for Low-Resource Languages—0
An Efficient Cross-lingual Model for Sentence Classification Using Convolutional Neural Network—0
An efficient domain-independent approach for supervised keyphrase extraction and ranking—0
An Embedding Model for Predicting Roll-Call Votes—0
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification—0
An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing—0
An Empirical Study of the Downstream Reliability of Pre-Trained Word Embeddings—0
An empirical study on large scale text classification with skip-gram embeddings—0
An Empirical Study on Post-processing Methods for Word Embeddings—0
An Empirical Study on Sentiment Classification of Chinese Review using Word Embedding—0
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