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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 2926–2950 of 4002 papers

TitleStatusHype
Multi-entity sentiment analysis using entity-level feature extraction and word embeddings approach—0
Multi-Granularity Chinese Word Embedding—0
Multi-level biomedical NER through multi-granularity embeddings and enhanced labeling—0
Multi-level Representations for Fine-Grained Typing of Knowledge Base Entities—0
Multilingual acoustic word embeddings for zero-resource languages—0
Multilingual Complex Word Identification: Convolutional Neural Networks with Morphological and Linguistic Features—0
Multilingual Culture-Independent Word Analogy Datasets—0
Multilingual Dependency Parsing for Low-Resource African Languages: Case Studies on Bambara, Wolof, and Yoruba—0
Multi-lingual Entity Discovery and Linking—0
Multilingual Learning for Mild Cognitive Impairment Screening from a Clinical Speech Task—0
Multi-lingual Mathematical Word Problem Generation using Long Short Term Memory Networks with Enhanced Input Features—0
Multilingual Model Using Cross-Task Embedding Projection—0
Multilingual, Multi-scale and Multi-layer Visualization of Intermediate Representations—0
Multilingual Offensive Language Identification for Low-resource Languages—0
Multilingual Query-by-Example Keyword Spotting with Metric Learning and Phoneme-to-Embedding Mapping—0
Multilingual segmentation based on neural networks and pre-trained word embeddings—0
Multilingual Sentiment Analysis: An RNN-Based Framework for Limited Data—0
Multilingual Seq2seq Training with Similarity Loss for Cross-Lingual Document Classification—0
Multilingual Training of Crosslingual Word Embeddings—0
Multilingual Visual Sentiment Concept Matching—0
Multilingual Word Embeddings for Low-Resource Languages using Anchors and a Chain of Related Languages—0
Multilingual Word Embeddings using Multigraphs—0
Multilingual Wordnet sense Ranking using nearest context—0
Multimedia Lab @ ACL WNUT NER Shared Task: Named Entity Recognition for Twitter Microposts using Distributed Word Representations—0
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations—0
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