Learning word vectors for 157 languages
Distributed word representations, or word vectors, have recently been applied to many tasks
in natural language processing, leading to state-of-the-art performance. A key ingredient to …
in natural language processing, leading to state-of-the-art performance. A key ingredient to …
Enriching word vectors with subword information
Continuous word representations, trained on large unlabeled corpora are useful for many
natural language processing tasks. Popular models that learn such representations ignore …
natural language processing tasks. Popular models that learn such representations ignore …
Word2vec convolutional neural networks for classification of news articles and tweets
Big web data from sources including online news and Twitter are good resources for
investigating deep learning. However, collected news articles and tweets almost certainly …
investigating deep learning. However, collected news articles and tweets almost certainly …
Attention-based long short-term memory network using sentiment lexicon embedding for aspect-level sentiment analysis in Korean
M Song, H Park, K Shin - Information Processing & Management, 2019 - Elsevier
Although deep learning breakthroughs in NLP are based on learning distributed word
representations by neural language models, these methods suffer from a classic drawback …
representations by neural language models, these methods suffer from a classic drawback …
[HTML][HTML] Deep neural networks reveal topic-level representations of sentences in medial prefrontal cortex, lateral anterior temporal lobe, precuneus, and angular gyrus
When reading a sentence, individual words can be combined to create more complex
meaning. In this study, we sought to uncover brain regions that reflect the representation of …
meaning. In this study, we sought to uncover brain regions that reflect the representation of …
General and feature-based semantic representations in the semantic network
How semantic representations are manifest over the brain remains a topic of active debate.
A semantic representation may be determined by specific semantic features (eg …
A semantic representation may be determined by specific semantic features (eg …
Iterative annotation of biomedical ner corpora with deep neural networks and knowledge bases
The large availability of clinical natural language documents, such as clinical narratives or
diagnoses, requires the definition of smart automatic systems for their processing and …
diagnoses, requires the definition of smart automatic systems for their processing and …
Subword-level word vector representations for Korean
Research on distributed word representations is focused on widely-used languages such as
English. Although the same methods can be used for other languages, language-specific …
English. Although the same methods can be used for other languages, language-specific …
Understanding the role of linguistic distributional knowledge in cognition
C Wingfield, L Connell - Language, Cognition and Neuroscience, 2022 - Taylor & Francis
The distributional pattern of words in language forms the basis of linguistic distributional
knowledge and contributes to conceptual processing, yet many questions remain regarding …
knowledge and contributes to conceptual processing, yet many questions remain regarding …
subs2vec: Word embeddings from subtitles in 55 languages
J Van Paridon, B Thompson - Behavior research methods, 2021 - Springer
This paper introduces a novel collection of word embeddings, numerical representations of
lexical semantics, in 55 languages, trained on a large corpus of pseudo-conversational …
lexical semantics, in 55 languages, trained on a large corpus of pseudo-conversational …