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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 2751–2800 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
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings—0
UMDuluth-CS8761 at SemEval-2018 Task 9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings—0
Lifelong Domain Word Embedding via Meta-LearningCode0
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling MechanismsCode0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
Scoring Lexical Entailment with a Supervised Directional Similarity NetworkCode0
How much does a word weigh? Weighting word embeddings for word sense induction—0
Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across LanguagesCode0
Aff2Vec: Affect--Enriched Distributional Word Representations—0
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token EncodingsCode0
Sentence Modeling via Multiple Word Embeddings and Multi-level Comparison for Semantic Textual Similarity—0
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces—0
Unsupervised Learning of Style-sensitive Word Vectors—0
Simplifying Sentences with Sequence to Sequence Models—0
Effects of Word Embeddings on Neural Network-based Pitch Accent Detection—0
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular MaximizationCode0
Analogical Reasoning on Chinese Morphological and Semantic RelationsCode0
New Embedded Representations and Evaluation Protocols for Inferring Transitive Relations—0
NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake—0
Domain Adapted Word Embeddings for Improved Sentiment ClassificationCode0
Learning Domain-Sensitive and Sentiment-Aware Word Embeddings—0
Adversarial Contrastive Estimation—0
Incorporating Subword Information into Matrix Factorization Word EmbeddingsCode0
Russian word sense induction by clustering averaged word embeddingsCode0
A Rank-Based Similarity Metric for Word Embeddings—0
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