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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 3526–3550 of 4002 papers

TitleStatusHype
Neural Structural Correspondence Learning for Domain AdaptationCode0
Chinese Event Extraction Using DeepNeural Network with Word Embedding—0
Are Word Embedding-based Features Useful for Sarcasm Detection?—0
Sentence Segmentation in Narrative Transcripts from Neuropsychological Tests using Recurrent Convolutional Neural Networks—0
基於相依詞向量的剖析結果重估與排序(N-best Parse Rescoring Based on Dependency-Based Word Embeddings)—0
Supervised Word Sense Disambiguation with Sentences Similarities from Context Word Embeddings—0
Topic Modeling over Short Texts by Incorporating Word EmbeddingsCode0
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks—0
emoji2vec: Learning Emoji Representations from their DescriptionCode0
Creating Causal Embeddings for Question Answering with Minimal Supervision—0
Ask the GRU: Multi-Task Learning for Deep Text Recommendations—0
Content Selection through Paraphrase Detection: Capturing different Semantic Realisations of the Same Idea—0
Hash2Vec, Feature Hashing for Word Embeddings—0
Testing APSyn against Vector Cosine on Similarity Estimation—0
Learning Word Embeddings from Intrinsic and Extrinsic Views—0
A Strong Baseline for Learning Cross-Lingual Word Embeddings from Sentence Alignments—0
Using Centroids of Word Embeddings and Word Mover's Distance for Biomedical Document Retrieval in Question Answering—0
Redefining part-of-speech classes with distributional semantic models—0
Resolving Out-of-Vocabulary Words with Bilingual Embeddings in Machine Translation—0
Bridging the Gap: Incorporating a Semantic Similarity Measure for Effectively Mapping PubMed Queries to Documents—0
UsingWord Embeddings for Query Translation for Hindi to English Cross Language Information Retrieval—0
Morphological Priors for Probabilistic Neural Word Embeddings—0
New word analogy corpus for exploring embeddings of Czech wordsCode0
Exponential Family Embeddings—0
How to Train good Word Embeddings for Biomedical NLPCode0
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