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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 2776–2800 of 4002 papers

TitleStatusHype
Lexicalized vs. Delexicalized Parsing in Low-Resource Scenarios—0
Lexical Relation Mining in Neural Word Embeddings—0
Lexical semantics enhanced neural word embeddings—0
Lexical Simplification with Neural Ranking—0
Lexical Simplification with the Deep Structured Similarity Model—0
Lexicon-Enhancement of Embedding-based Approaches Towards the Detection of Abusive Language—0
Lexicon Infused Phrase Embeddings for Named Entity Resolution—0
Lexicon Integrated CNN Models with Attention for Sentiment Analysis—0
LIA at SemEval-2017 Task 4: An Ensemble of Neural Networks for Sentiment Classification—0
Lifelong Word Embedding via Meta-Learning—0
LightRel at SemEval-2018 Task 7: Lightweight and Fast Relation Classification—0
LightRel SemEval-2018 Task 7: Lightweight and Fast Relation Classification—0
Lightweight Efficient Multi-keyword Ranked Search over Encrypted Cloud Data using Dual Word Embeddings—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
LIMSI-COT at SemEval-2016 Task 12: Temporal relation identification using a pipeline of classifiers—0
Line-a-line: A Tool for Annotating Word-Alignments—0
Linguistic change and historical periodization of Old Literary Finnish—0
Linguistic Regularities in Sparse and Explicit Word Representations—0
Linking News Sentiment to Microblogs: A Distributional Semantics Approach to Enhance Microblog Sentiment Classification—0
Linking Tweets with Monolingual and Cross-Lingual News using Transformed Word Embeddings—0
LIPN-IIMAS at SemEval-2016 Task 1: Random Forest Regression Experiments on Align-and-Differentiate and Word Embeddings penalizing strategies—0
LIPN-IIMAS at SemEval-2017 Task 1: Subword Embeddings, Attention Recurrent Neural Networks and Cross Word Alignment for Semantic Textual Similarity—0
LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination—0
LIS at SemEval-2018 Task 2: Mixing Word Embeddings and Bag of Features for Multilingual Emoji Prediction—0
Literal, Metphorical or Both? Detecting Metaphoricity in Isolated Adjective-Noun Phrases—0
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