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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 3026–3050 of 4002 papers

TitleStatusHype
New Product Development (NPD) through Social Media-based Analysis by Comparing Word2Vec and BERT Word Embeddings—0
Ngram2vec: Learning Improved Word Representations from Ngram Co-occurrence Statistics—0
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning—0
NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis—0
NLP Analytics in Finance with DoRe: A French 250M Tokens Corpus of Corporate Annual Reports—0
NLP and Education: using semantic similarity to evaluate filled gaps in a large-scale Cloze test in the classroom—0
NLP@UNED at SMM4H 2019: Neural Networks Applied to Automatic Classifications of Adverse Effects Mentions in Tweets—0
NNEMBs at SemEval-2017 Task 4: Neural Twitter Sentiment Classification: a Simple Ensemble Method with Different Embeddings—0
Noisy Parallel Corpus Filtering through Projected Word Embeddings—0
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input—0
Non-Complementarity of Information in Word-Embedding and Brain Representations in Distinguishing between Concrete and Abstract Words—0
Non-Euclidean Hierarchical Representational Learning using Hyperbolic Graph Neural Networks for Environmental Claim Detection—0
Non-Linear Instance-Based Cross-Lingual Mapping for Non-Isomorphic Embedding Spaces—0
Non-Linearity in Mapping Based Cross-Lingual Word Embeddings—0
Non-Linear Relational Information Probing in Word Embeddings—0
Nonsymbolic Text Representation—0
Normalization of Transliterated Words in Code-Mixed Data Using Seq2Seq Model \& Levenshtein Distance—0
NORMA: Neighborhood Sensitive Maps for Multilingual Word Embeddings—0
NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction—0
Norm of Word Embedding Encodes Information Gain—0
NormXLogit: The Head-on-Top Never Lies—0
Not just about size - A Study on the Role of Distributed Word Representations in the Analysis of Scientific Publications—0
Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models—0
NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake—0
NRC: Infused Phrase Vectors for Named Entity Recognition in Twitter—0
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