Results 1 to 10 of about 11,306 (258)

Word embeddings as autonomous predictors in materials design—the effect of inherent variability on information transfer [PDF]

Journal of Cheminformatics
We propose that word embeddings of atoms derived from scientific literature are revisited as autonomous machine learning predictors in materials design.
Jana Radaković, Katarina Batalović, Nikola Novaković   +2 more
doaj   +2 more sources

Word Embeddings as Statistical Estimators. [PDF]

Sankhya Ser B
Word embeddings are a fundamental tool in natural language processing. Currently, word embedding methods are evaluated on the basis of empirical performance on benchmark data sets, and there is a lack of rigorous understanding of their theoretical properties.
Dey N, Singer M, Williams JP, Sengupta S.   +3 more
europepmc   +5 more sources

Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish [PDF]

Frontiers in Artificial Intelligence, 2022
Resources for Natural Language Processing (NLP) are less numerous for languages different from English. In the clinical domain, where these resources are vital for obtaining new knowledge about human health and diseases, creating new resources for the ...
Carolina Chiu, Fabián Villena, Fabián Villena, Kinan Martin, Fredy Núñez, Fredy Núñez, Cecilia Besa, Cecilia Besa, Jocelyn Dunstan, Jocelyn Dunstan, Jocelyn Dunstan   +10 more
doaj   +2 more sources

Using word embeddings to investigate cultural biases [PDF]

British Journal of Social Psychology, 2023
Durrheim K, Schuld M, Mafunda M, Mazibuko S.   +3 more
exaly   +2 more sources

Comparing general and specialized word embeddings for biomedical named entity recognition [PDF]

PeerJ Computer Science, 2021
Increased interest in the use of word embeddings, such as word representation, for biomedical named entity recognition (BioNER) has highlighted the need for evaluations that aid in selecting the best word embedding to be used.
Rigo E. Ramos-Vargas, Israel Román-Godínez, Sulema Torres-Ramos   +2 more
doaj   +2 more sources

Historical representations of social groups across 200 years of word embeddings from Google Books [PDF]

Proceedings of the National Academy of Sciences of the United States of America, 2022
Tessa Charlesworth, Aylin Caliskan, Mahzarin Banaji   +2 more
exaly   +2 more sources

Improved biomedical word embeddings in the transformer era [PDF]

Journal of Biomedical Informatics, 2021
Jiho Noh, Ramakanth Kavuluru
exaly   +2 more sources

Deterministic Compression of Word Embeddings

IEEE Access
Word embeddings are an indispensable technology in the field of artificial intelligence, particularly when working with natural language processing models.
Yuki Nakamura, Jun Suzuki, Takumi Ito, Kentaro Inui   +3 more
doaj   +2 more sources

Bias in word embeddings [PDF]

Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020
Word embeddings are a widely used set of natural language processing techniques that map words to vectors of real numbers. These vectors are used to improve the quality of generative and predictive models. Recent studies demonstrate that word embeddings contain and amplify biases present in data, such as stereotypes and prejudice.
Orestis Papakyriakopoulos, Simon Hegelich, Juan Carlos Medina Serrano, Fabienne Marco   +3 more
openaire   +1 more source

Clustering and Visualising Documents using Word Embeddings

The Programming Historian, 2023
This lesson uses word embeddings and clustering algorithms in Python to identify groups of similar documents in a corpus of approximately 9,000 academic abstracts.
Jonathan Reades, Jennie Williams
doaj   +1 more source