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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 2751–2775 of 4002 papers

TitleStatusHype
Context Sensitive Neural Lemmatization with Lematus—0
How Gender and Skin Tone Modifiers Affect Emoji Semantics in TwitterCode0
ABDN at SemEval-2018 Task 10: Recognising Discriminative Attributes using Context Embeddings and WordNet—0
TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields—0
Entropy-Based Subword Mining with an Application to Word Embeddings—0
\#TeamINF at SemEval-2018 Task 2: Emoji Prediction in Tweets—0
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic—0
ELiRF-UPV at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge—0
Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes—0
Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets—0
Learning Word Embeddings for Low-Resource Languages by PU Learning—0
EICA Team at SemEval-2018 Task 2: Semantic and Metadata-based Features for Multilingual Emoji Prediction—0
ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection—0
Pay-Per-Request Deployment of Neural Network Models Using Serverless Architectures—0
The UWNLP system at SemEval-2018 Task 7: Neural Relation Extraction Model with Selectively Incorporated Concept Embeddings—0
The Word Analogy Testing Caveat—0
Peperomia at SemEval-2018 Task 2: Vector Similarity Based Approach for Emoji Prediction—0
DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction—0
THU\_NGN at SemEval-2018 Task 10: Capturing Discriminative Attributes with MLP-CNN model—0
SB@GU at the Complex Word Identification 2018 Shared Task—0
What the Vec? Towards Probabilistically Grounded Embeddings—0
Multi-turn Dialogue Response Generation in an Adversarial Learning Framework—0
Quantum-inspired Complex Word Embedding—0
Unsupervised Alignment of Embeddings with Wasserstein ProcrustesCode0
Unsupervised detection of diachronic word sense evolution—0
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