Results 41 to 50 of about 37,068 (209)
NASARI: a novel approach to a Semantically-Aware Representation of items [PDF]
, 2015 The semantic representation of individual word senses and concepts is of fundamental importance to several applications in Natural Language Processing.
CAMACHO COLLADOS, Jose' +2 more
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British Journal of Psychology, EarlyView.Abstract Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye‐tracking and compared their attention strategies ...
Ruoxi Qi +4 more
wiley +1 more source
Multi-Class Document Classification Using Lexical Ontology-Based Deep Learning
Applied Sciences, 2023 With the recent growth of the Internet, the volume of data has also increased. In particular, the increase in the amount of unstructured data makes it difficult to manage data. Classification is also needed in order to be able to use the data for various
Ilkay Yelmen, Ali Gunes, Metin Zontul
doaj +1 more source
Semantics-based selection of everyday concepts in visual lifelogging [PDF]
, 2012 Concept-based indexing, based on identifying various semantic concepts appearing in multimedia, is an attractive option for multimedia retrieval and much research tries to bridge the semantic gap between the media’s low-level features and high-level ...
Smeaton, Alan F., Wang, Peng
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Using GPT‐4 to Augment Imbalanced Data for Automatic Scoring
Journal of Educational Measurement, EarlyView.Abstract Machine learning‐based automatic scoring faces challenges with imbalanced student responses across scoring categories. To address this, we introduce a novel text data augmentation framework that leverages GPT‐4, a generative large language model specifically tailored for imbalanced datasets in automatic scoring.
Luyang Fang +2 more
wiley +1 more source
Human tests for machine models: What lies “Beyond the Imitation Game”?
Journal of Linguistic Anthropology, EarlyView.Abstract Benchmarking large language models (LLMs) is a key practice for evaluating their capabilities and risks. This paper considers the development of “BIG Bench,” a crowdsourced benchmark designed to test LLMs “Beyond the Imitation Game.” Drawing on linguistic anthropological and ethnographic analysis of the project's GitHub repository, we examine ...
Noya Kohavi, Anna Weichselbraun
wiley +1 more source
Utemeljevanje sloWNeta na korpusnih podatkih
Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, 2013 Wordnet lahko izdelamo na podlagi že obstoječega tujejezičnega wordneta ali pa kot osnovo za gradnjo vzamemo korpusne podatke. Prvi pristop je preprostejši in enostavnejši, zaradi česar ga razvijalci tudi najpogosteje uporabljajo.
Darja Fišer +2 more
doaj +1 more source
3DText: Perceiving sentence-level text on 3-D model of emotions
Engineering and Applied Science Research, 2020 Emotion is a psychological process which reveals the sentiments and feelings of a human being. Relating emotions detection process with psychological theory of emotions serves as the strong foundation for the system.
Shalu Choudhary, Shikha Jain
doaj +1 more source
Medical WordNet: A new methodology for the construction and validation of information resources for consumer health [PDF]
, 2004 A consumer health information system must be able to comprehend both expert and non-expert medical vocabulary and to map between the two. We describe an ongoing project to create a new lexical database called Medical WordNet (MWN), consisting ...
Fellbaum, Christiane, Smith, Barry
core
Web 2.0, language resources and standards to automatically build a multilingual named entity lexicon [PDF]
, 2011 This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) building by taking into consideration three elements: (i) the knowledge available in existing LRs, (ii) the vast amount of information available from the ...
Ferrández, Sergio +3 more
core +1 more source