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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 3051–3100 of 4002 papers

TitleStatusHype
Predicting Pronouns with a Convolutional Network and an N-gram Model—0
Predicting Word Association Strengths—0
Prepositional Phrase Attachment over Word Embedding Products—0
MEANT 2.0: Accurate semantic MT evaluation for any output language—0
LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination—0
Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model—0
Recognizing Textual Entailment in Twitter Using Word Embeddings—0
Lexicalized vs. Delexicalized Parsing in Low-Resource Scenarios—0
Lexical Chains meet Word Embeddings in Document-level Statistical Machine Translation—0
Refining Word Embeddings for Sentiment Analysis—0
LCT-MALTA's Submission to RepEval 2017 Shared Task—0
Knowledge Distillation for Bilingual Dictionary Induction—0
Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees—0
Joint Embeddings of Chinese Words, Characters, and Fine-grained Subcharacter Components—0
Investigating neural architectures for short answer scoring—0
Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings—0
Inter-Weighted Alignment Network for Sentence Pair Modeling—0
Improving neural tagging with lexical information—0
Sentiment Intensity Ranking among Adjectives Using Sentiment Bearing Word Embeddings—0
Sentiment Lexicon Construction with Representation Learning Based on Hierarchical Sentiment SupervisionCode0
IITP at EmoInt-2017: Measuring Intensity of Emotions using Sentence Embeddings and Optimized Features—0
Identifying attack and support argumentative relations using deep learning—0
Gender Prediction for Chinese Social Media Data—0
Fully Delexicalized Contexts for Syntax-Based Word Embeddings—0
Finding Individual Word Sense Changes and their Delay in Appearance—0
Extracting Tags from Large Raw Texts Using End-to-End Memory Networks—0
Exploring Vector Spaces for Semantic Relations—0
Exploiting Morphological Regularities in Distributional Word Representations—0
Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks—0
Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets—0
Earth Mover's Distance Minimization for Unsupervised Bilingual Lexicon Induction—0
Dual Tensor Model for Detecting Asymmetric Lexico-Semantic Relations—0
The strange geometry of skip-gram with negative sampling—0
Distinguishing Japanese Non-standard Usages from Standard Ones—0
Discovering Stylistic Variations in Distributional Vector Space Models via Lexical Paraphrases—0
Dict2vec : Learning Word Embeddings using Lexical DictionariesCode0
Detecting Sarcasm Using Different Forms Of Incongruity—0
Detecting Metaphorical Phrases in the Polish Language—0
Towards a Universal Sentiment Classifier in Multiple languages—0
Deriving continous grounded meaning representations from referentially structured multimodal contexts—0
Towards Lexical Chains for Knowledge-Graph-based Word Embeddings—0
Towards the Understanding of Gaming Audiences by Modeling Twitch Emotes—0
Deeper Attention to Abusive User Content Moderation—0
Cross-Lingual Word Representations: Induction and Evaluation—0
Cross-Lingual Transfer Learning for POS Tagging without Cross-Lingual Resources—0
Cross-Lingual Pronoun Prediction with Deep Recurrent Neural Networks v2.0—0
Translating Dialectal Arabic as Low Resource Language using Word Embedding—0
Character and Subword-Based Word Representation for Neural Language Modeling Prediction—0
C-3MA: Tartu-Riga-Zurich Translation Systems for WMT17Code0
Using Gaze Data to Predict Multiword Expressions—0
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