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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 1976–2000 of 4002 papers

TitleStatusHype
Evaluation of Word Embeddings for the Social Sciences—0
It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution—0
IxaMed at PharmacoNER Challenge 2019—0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
Evaluation of Taxonomy Enrichment on Diachronic WordNet Versions—0
Japanese Lexical Simplification for Non-Native Speakers—0
Japanese Word Readability Assessment using Word Embeddings—0
Evaluation of Stacked Embeddings for Bulgarian on the Downstream Tasks POS and NERC—0
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena—0
Classifying Out-of-vocabulary Terms in a Domain-Specific Social Media Corpus—0
JHU System Description for the MADAR Arabic Dialect Identification Shared Task—0
A Review on Deep Learning Techniques Applied to Answer Selection—0
Joint Embeddings of Chinese Words, Characters, and Fine-grained Subcharacter Components—0
Evaluation of Question Answering Systems: Complexity of judging a natural language—0
Joint Learning from Labeled and Unlabeled Data for Information Retrieval—0
Evaluation of Morphological Embeddings for the Russian Language—0
Joint Learning of Hierarchical Word Embeddings from a Corpus and a Taxonomy—0
Evaluation of Greek Word Embeddings—0
Joint Learning of Word and Label Embeddings for Sequence Labelling in Spoken Language Understanding—0
Jointly Learning to Embed and Predict with Multiple Languages—0
JOINTLY LEARNING TOPIC SPECIFIC WORD AND DOCUMENT EMBEDDING—0
Classification of Micro-Texts Using Sub-Word Embeddings—0
Jointly modelling the evolution of social structure and language in online communities—0
A Review of Standard Text Classification Practices for Multi-label Toxicity Identification of Online Content—0
A Locally Linear Procedure for Word Translation—0
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