Results 71 to 80 of about 824,215 (366)
Advanced Engineering Materials, EarlyView.This article provides examples of ontology development in the materials science domain (use‐case of Brinell hardness testing) and gives ontology developers an overview for selecting their desired top‐level ontologies (e.g., BFO, EMMO, PROVO) by considering different evaluation parameters like semantic richness, domain coverage, extensibility ...
Hossein Beygi Nasrabadi +3 more
wiley +1 more source
Three-way Decisions with Evaluative Linguistic Expressions [PDF]
arXiv, 2023 We propose a linguistic interpretation of three-way decisions, where the regions of acceptance, rejection, and non-commitment are constructed by using the so-called evaluative linguistic expressions, which are expressions of natural language such as small, medium, very short, quite roughly strong, extremely good, etc.
arxiv
Linguistic variation and computation [PDF]
Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - EACL '03, 2003 Language variationists, study how languages vary along geographical or social lines or along lines of age and gender. Variationist data is available and challenging, in particular for DIALECTOLOGY, the study of geographical variation, which will be the focus of this paper, although we present approaches we expect to transfer smoothly to the study of ...
openaire +3 more sources
Advanced Intelligent Systems, EarlyView.Recent advancements in wearable healthcare have brought accessible continuous glucose monitoring systems (CGMs) for diabetes management. To address the limitations of CGMs, closed‐loop systems utilizing monitored glucose levels for insulin dosing are being developed.
Wei Huang +5 more
wiley +1 more source
Morphemic Structure of Lithuanian Words
Open Linguistics, 2016 The Lithuanian language is a typical flectional language that has a very sophisticated system of grammatical forms and many means of derivation; it is also characterized by uncertain boundaries between morphemes.
Rimkutė Erika +2 more
doaj +1 more source
Scaling and Disagreements: Bias, Noise, and Ambiguity
Frontiers in Artificial Intelligence, 2022 Crowdsourced data are often rife with disagreement, either because of genuine item ambiguity, overlapping labels, subjectivity, or annotator error. Hence, a variety of methods have been developed for learning from data containing disagreement. One of the
Alexandra Uma +4 more
doaj +1 more source
Linguistics in computational linguistics [PDF]
Proceedings of the EACL 2009 Workshop on the Interaction between Linguistics and Computational Linguistics Virtuous, Vicious or Vacuous? - ILCL '09, 2009 As my title suggests, this position paper focuses on the relevance of linguistics in NLP instead of asking the inverse question. Although the question about the role of computational linguistics in the study of language may theoretically be much more interesting than the selected topic, I feel that my choice is more appropriate for the purpose and ...
openaire +2 more sources
Linguistic Markers of Influence in Informal Interactions
, 2017 There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily interactions. Motivated
Black, Alan W +5 more
core +1 more source
Journal of the Association for Information Science and Technology, EarlyView.Abstract This paper investigates the use of multimedia verification, in particular, computational tools and Open‐source Intelligence (OSINT) methods, for verifying online multimedia content in the context of the ongoing wars in Ukraine and Gaza. Our study examines the workflows and tools used by several fact‐checkers and journalists working at Faktisk,
Sohail Ahmed Khan +6 more
wiley +1 more source
Death by AI: Will large language models diminish Wikipedia?
Journal of the Association for Information Science and Technology, EarlyView.Abstract We argue that advances in large language models (LLMs) and generative Artificial Intelligence (AI) will diminish the value of Wikipedia, due to a withdrawal by human content producers, who will withhold their efforts, perceiving less need for their efforts and increased “AI competition.” We believe the greatest threat to Wikipedia stems from ...
Christian Wagner, Ling Jiang
wiley +1 more source