Gaze-based Opportunistic Privacy-preserving Human-Agent Collaboration
Type
conference contribution
Date Issued
2024-05-11
Author(s)
Research Team
Interaction- and Communication-based Systems (https://interactions.ics.unisg.ch)
Abstract
This paper introduces a novel system to enhance the spatiotemporal alignment of human abilities in agent-based workflows. This optimization is realized through the application of Linked Data and Semantic Web technologies and the system makes use of gaze data and contextual information. The showcased prototype demonstrates the feasibility of implementing such a system, where we specifically emphasize the system’s ability to constrain the dissemination of privacy-relevant information.
Language
English (United States)
Keywords
Human-Agent-Collaboration
Solid
Koreografeye
Privacy
Semantic Web
Gaze
Notifications
Innovation
HSG Classification
contribution to scientific community
Refereed
Yes
Book title
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24)
Publisher
ACM
Publisher place
New York, NY, USA
Pages
7
Event Title
CHI Conference on Human Factors in Computing Systems (CHI ’24)
Event Location
Honolulu, HI, USA
Event Date
May 11-16, 2024
Official URL
Subject(s)
Division(s)
Contact Email Address
jan.grau@student.unisg.ch
File(s)![Thumbnail Image]()
open.access
Name
Grau et al_2024_Gaze_Based_Opportunistic_Notification_System_for_Human_Agent_Collaboration.pdf
Size
3.93 MB
Format
Adobe PDF
Checksum (MD5)
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