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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 3201–3225 of 4002 papers

TitleStatusHype
SINAI at SemEval-2017 Task 4: User based classification—0
Semantic Frame Labeling with Target-based Neural Model—0
TakeLab at SemEval-2017 Task 4: Recent Deaths and the Power of Nostalgia in Sentiment Analysis in Twitter—0
Parsing with Context Embeddings—0
ECNU at SemEval-2017 Task 4: Evaluating Effective Features on Machine Learning Methods for Twitter Message Polarity Classification—0
A Semi-universal Pipelined Approach to the CoNLL 2017 UD Shared Task—0
Zero-Inflated Exponential Family Embeddings—0
Learning Antonyms with Paraphrases and a Morphology-Aware Neural Network—0
RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list—0
What Analogies Reveal about Word Vectors and their Compositionality—0
SZTE-NLP at SemEval-2017 Task 10: A High Precision Sequence Model for Keyphrase Extraction Utilizing Sparse Coding for Feature Generation—0
The (too Many) Problems of Analogical Reasoning with Word Vectors—0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation—0
Adapting Pre-trained Word Embeddings For Use In Medical Coding—0
SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity—0
funSentiment at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs Using Word Vectors Built from StockTwits and Twitter—0
funSentiment at SemEval-2017 Task 4: Topic-Based Message Sentiment Classification by Exploiting Word Embeddings, Text Features and Target Contexts—0
Cross-Lingual Classification of Topics in Political Texts—0
Cross-language Learning with Adversarial Neural Networks—0
From Raw Text to Universal Dependencies - Look, No Tags!—0
A System for Multilingual Dependency Parsing based on Bidirectional LSTM Feature Representations—0
Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job DescriptionCode0
Analysis of Italian Word Embeddings—0
Temporal dynamics of semantic relations in word embeddings: an application to predicting armed conflict participants—0
From Image to Text Classification: A Novel Approach based on Clustering Word Embeddings—0
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