Results 221 to 230 of about 83,408 (318)
Using Eye Movements From a “Read‐Only” Task to Predict Text Comprehension
Reading Research Quarterly, Volume 60, Issue 3, July/September 2025.ABSTRACT Recent research on the use of eye movements to predict performance on reading comprehension tasks suggests that while eye movements may be used to measure comprehension, the relationship between eye‐movement behavior and comprehension is influenced by differences in task demands between comprehension measures.
Diane C. Mézière +4 more
wiley +1 more source
The Noisy Channel Model for Unsupervised Word Sense Disambiguation
Computational Linguistics, 2021 Deniz Yuret, Mehmet Ali Yatbaz
doaj +1 more source
Word Sense Disambiguation and WordNet Technology [PDF]
, 2008 Satanjeev Banerjee, B. P. Mullick
openalex +1 more source
Word Sense Disambiguation for clinical abbreviations
, 2022 Las abreviaturas se utilizan ampliamente en las historias clínicas electrónicas de los pacientes y en mucha documentación médica, llegando a ser un 30-50% de las palabras empleadas en narrativa clínica. Existen más de 197.000 abreviaturas únicas usadas en textos clínicos siendo términos altamente ambiguos El significado de las abreviaturas varía en ...
openaire +2 more sources
International Journal of Consumer Studies, Volume 49, Issue 4, July 2025.ABSTRACT Contributing to a burgeoning area of research on the nuanced effects of emojis in brand communications, the current research builds understanding of two dominant forms of emoji role—emojis as text reinforcement and emojis as text substitution—and their downstream effects. Across three studies, we examine how emoji roles differentially interact
Qi Deng, Lindsay McShane
wiley +1 more source
Human Brain Mapping, Volume 46, Issue 9, June 15, 2025.Brain iron deposition in the caudate and putamen is elevated in Type 2 diabetes mellitus (T2DM) and mediates the link between blood glucose fluctuations and cognitive decline. These findings highlight iron homeostasis disruption as a key mechanism in T2DM‐related cognitive impairment, suggesting potential targets for early intervention. ABSTRACT Type 2
Zhenyu Cheng +13 more
wiley +1 more source
Applying active learning to supervised word sense disambiguation in MEDLINE. [PDF]
J Am Med Inform Assoc, 2013 Chen Y, Cao H, Mei Q, Zheng K, Xu H.
europepmc +1 more source
A combination of active learning and semi-supervised learning starting with positive and unlabeled examples for word sense disambiguation [PDF]
, 2009 Makoto Imamura +4 more
openalex +1 more source
Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods. [PDF]
J Am Med Inform Assoc, 2014 Chasin R +3 more
europepmc +1 more source