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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 726–750 of 4002 papers

TitleStatusHype
CLFD: A Novel Vectorization Technique and Its Application in Fake News Detection—0
Clickbait detection using word embeddings—0
Clinical Abbreviation Disambiguation Using Neural Word Embeddings—0
“Are you calling for the vaporizer you ordered?” Combining Search and Prediction to Identify Orders in Contact Centers—0
Clinical Event Detection with Hybrid Neural Architecture—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
Clinical Named Entity Recognition using Contextualized Token Representations—0
Boosting Named Entity Recognition with Neural Character Embeddings—0
ArGoT: A Glossary of Terms extracted from the arXiv—0
CLULEX at SemEval-2021 Task 1: A Simple System Goes a Long Way—0
Argumentative Topology: Finding Loop(holes) in Logic—0
Clustering Comparable Corpora of Russian and Ukrainian Academic Texts: Word Embeddings and Semantic Fingerprints—0
Clustering is Efficient for Approximate Maximum Inner Product Search—0
Argument from Old Man’s View: Assessing Social Bias in Argumentation—0
Clustering of Russian Adjective-Noun Constructions using Word Embeddings—0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora—0
ARHNet - Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic—0
An Unsupervised Approach for Mapping between Vector Spaces—0
Cluster Labeling by Word Embeddings and WordNet's Hypernymy—0
Comparison of Representations of Named Entities for Document Classification—0
CNN- and LSTM-based Claim Classification in Online User Comments—0
BLISS in Non-Isometric Embedding Spaces—0
Blinov: Distributed Representations of Words for Aspect-Based Sentiment Analysis at SemEval 2014—0
Code-Switched Named Entity Recognition with Embedding Attention—0
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence—0
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