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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 1451–1500 of 4002 papers

TitleStatusHype
Query Focused Multi-document Summarisation of Biomedical TextsCode0
Multimodal Learning for Cardiovascular Risk Prediction using EHR Data—0
Query Focused Multi-document Summarisation of Biomedical Texts: Macquarie Universiy and the Australian National University at BioASQ8bCode0
Contextualized moral inference—0
Simple Unsupervised Similarity-Based Aspect ExtractionCode0
Two Stages Approach for Tweet Engagement Prediction—0
Predicting Helpfulness of Online Reviews—0
An Experimental Study of Deep Neural Network Models for Vietnamese Multiple-Choice Reading Comprehension—0
A Survey of Active Learning for Text Classification using Deep Neural Networks—0
MICE: Mining Idioms with Contextual EmbeddingsCode0
Context Reinforced Neural Topic Modeling over Short TextsCode0
A Neural Generative Model for Joint Learning Topics and Topic-Specific Word EmbeddingsCode0
An exploration of the encoding of grammatical gender in word embeddings—0
Deep Learning based Topic Analysis on Financial Emerging Event Tweets—0
Combining Representations For Effective Citation ClassificationCode0
Unsupervised Deep Cross-modality Spectral Hashing—0
Word embedding and neural network on grammatical gender -- A case study of Swedish—0
Effect of Text Processing Steps on Twitter Sentiment Classification using Word Embedding—0
Word Embeddings: Stability and Semantic Change—0
IITK at the FinSim Task: Hypernym Detection in Financial Domain via Context-Free and Contextualized Word Embeddings—0
Predicting Job-Hopping Motive of Candidates Using Answers to Open-ended Interview Questions—0
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification—0
Morphological Skip-Gram: Using morphological knowledge to improve word representation—0
On a Novel Application of Wasserstein-Procrustes for Unsupervised Cross-Lingual LearningCode0
An Enhanced Text Classification to Explore Health based Indian Government Policy Tweets—0
A Feature Analysis for Multimodal News Retrieval—0
Topic Modeling on User Stories using Word Mover's DistanceCode0
Pre-trained Word Embeddings for Goal-conditional Transfer Learning in Reinforcement Learning—0
Cultural Cartography with Word Embeddings—0
Automatic Detection of Sexist Statements Commonly Used at the WorkplaceCode0
Contextualized Spoken Word Representations from Convolutional Autoencoders—0
Reflection-based Word Attribute TransferCode0
Tweets Sentiment Analysis via Word Embeddings and Machine Learning Techniques—0
Explainable Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media—0
Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings—0
Predicting Degrees of Technicality in Automatic Terminology Extraction—0
Automated Scoring of Clinical Expressive Language Evaluation Tasks—0
Metaphor Detection Using Contextual Word Embeddings From Transformers—0
Adversarial Evaluation of BERT for Biomedical Named Entity Recognition—0
Analyzing the Framing of 2020 Presidential Candidates in the News—0
COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?—0
CopyBERT: A Unified Approach to Question Generation with Self-Attention—0
Neural Metaphor Detection with a Residual biLSTM-CRF Model—0
Neural-DINF: A Neural Network based Framework for Measuring Document Influence—0
Contextual and Non-Contextual Word Embeddings: an in-depth Linguistic Investigation—0
Whole-Word Segmental Speech Recognition with Acoustic Word EmbeddingsCode0
Quantifying 60 Years of Gender Bias in Biomedical Research with Word Embeddings—0
Adaptive Compression of Word Embeddings—0
Getting the \#\#life out of living: How Adequate Are Word-Pieces for Modelling Complex Morphology?—0
Improving Biomedical Analogical Retrieval with Embedding of Structural Dependencies—0
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