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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 2976–3000 of 4002 papers

TitleStatusHype
A mostly unlexicalized model for recognizing textual entailment—0
Amplifying the Range of News Stories with Creativity: Methods and their Evaluation, in Portuguese—0
Amrita\_CEN at SemEval-2016 Task 1: Semantic Relation from Word Embeddings in Higher Dimension—0
A Multidimensional Lexicon for Interpersonal Stancetaking—0
A Multi-Domain Framework for Textual Similarity. A Case Study on Question-to-Question and Question-Answering Similarity Tasks—0
A multilabel approach to morphosyntactic probing—0
A Multilayer Perceptron based Ensemble Technique for Fine-grained Financial Sentiment Analysis—0
A multi-level approach for hierarchical Ticket Classification—0
A Multimodal Approach towards Emotion Recognition of Music using Audio and Lyrical Content—0
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations—0
A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases—0
A Multi-task Approach to Learning Multilingual Representations—0
A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition—0
A Multitask Objective to Inject Lexical Contrast into Distributional Semantics—0
A Multi-tiered Solution for Personalized Baggage Item Recommendations using FastText and Association Rule Mining—0
Analogical Proportions and Creativity: A Preliminary Study—0
Analogies Explained: Towards Understanding Word Embeddings—0
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.—0
Analysis of Gender Bias in Social Perception and Judgement Using Chinese Word Embeddings—0
Analysis of Inferences in Chinese for Opinion Mining—0
Analysis of Italian Word Embeddings—0
Analysis of Word Embeddings and Sequence Features for Clinical Information Extraction—0
Analysis of Word Embeddings Using Fuzzy Clustering—0
Analyzing Acoustic Word Embeddings from Pre-trained Self-supervised Speech Models—0
Analyzing autoencoder-based acoustic word embeddings—0
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