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Titlebook: HCI International 2024 Posters; 26th International C Constantine Stephanidis,Margherita Antona,Gavriel Conference proceedings 2024 The Edi

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31#
發(fā)表于 2025-3-26 23:01:44 | 只看該作者
32#
發(fā)表于 2025-3-27 04:01:30 | 只看該作者
Expert Perspectives on?UX Design Challenges for?Solid-Enabled Personal Data Store Applicationsing these challenges. We conclude by proposing a research agenda focusing on three key areas: 1) enhancing explainability, 2) investigating the balance between data control and usability, and 3) developing standardized design patterns.
33#
發(fā)表于 2025-3-27 08:51:24 | 只看該作者
34#
發(fā)表于 2025-3-27 13:14:05 | 只看該作者
35#
發(fā)表于 2025-3-27 16:32:39 | 只看該作者
1865-0929 ; Interaction in the Museum; HCI in Healthcare...Part VII: AI Algorithms and Tools in HCI; Interacting with Large Language Models and Generative AI; Interacting978-3-031-61965-6978-3-031-61966-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
36#
發(fā)表于 2025-3-27 20:28:14 | 只看該作者
https://doi.org/10.1057/9780230288430practical methodology to develop an automatic verbalizer using variants of the k-nearest neighbors (KNN) classifier..The proposed approach does not rely on a predefined dictionary. It predicts an aspect opinion using contextualized embedding vectors which encompass the information from the opinion-b
37#
發(fā)表于 2025-3-27 23:30:33 | 只看該作者
38#
發(fā)表于 2025-3-28 02:59:21 | 只看該作者
39#
發(fā)表于 2025-3-28 07:12:56 | 只看該作者
Life Satisfaction and Quality of Life,idering that contemporary artificial intelligence (AI) systems heavily rely on this extensive data, this investigation holds promise in illuminating optimal strategies for harnessing big data within diverse modern e-learning frameworks, all of which are underpinned by AI methodologies..Literature [.
40#
發(fā)表于 2025-3-28 12:21:07 | 只看該作者
Rob P. J. van Hees,Silvia Naldinigap, this study draws on data from the Korea Media Panel Survey 2022 and utilizes Latent Profile Analysis (LPA) to classify individuals based on their social media behaviors. LPA’s person-centered approach identifies five distinct user groups: light users, lurkers, casual users, likers, and network
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