Date
2019Metadata
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Konferenzveröffentlichung
Classifying Smart Personal Assistants: An Empirical Cluster Analysis
Abstract
The digital age has yielded systems that increasingly reduce the complexity of our everyday lives. As such, smart personal assistants such as Amazon’s Alexa or Apple’s Siri combine the comfort of intuitive natural language interaction with the utility of personalized and situation-dependent information and service provision. However, research on SPAs is becoming increasingly complex and opaque. To reduce complexity, this paper introduces a classification system for SPAs. Based on a systematic literature review, a cluster analysis reveals five SPA archetypes: Adaptive Voice (Vision) Assistants, Chatbot Assistants, Embodied Virtual Assistants, Passive Pervasive Assistants, and Natural Conversation Assistants.
Citation
In: Hawaii International Conference on System Sciences 2019 (Hrsg.): Proceedings of the 52rd Annual Hawaii International Conference on System Sciences. University of Hawaii at Manoa, Hamilton Library, ScholarSpace: Honolulu, Hawaii 2019, S. 2024-2033; ISBN 978-0-9981331-2-6Citation
@inproceedings{doi:10.17170/kobra-202010302037,
author={Knote, Robin and Janson, Andreas and Söllner, Matthias and Leimeister, Jan Marco},
title={Classifying Smart Personal Assistants: An Empirical Cluster Analysis},
booktitle={Proceedings of the 52rd Annual Hawaii International Conference on System Sciences},
year={2019}
}
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2020-11-02T14:46:56Z 2020-11-02T14:46:56Z 2019 doi:10.17170/kobra-202010302037 http://hdl.handle.net/123456789/11915 eng University of Hawaii at Manoa, Hamilton Library, ScholarSpace Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ decision analytics mobile services service science smart personal assistants intelligent agents classification cluster analysis literature review 004 Classifying Smart Personal Assistants: An Empirical Cluster Analysis Konferenzveröffentlichung The digital age has yielded systems that increasingly reduce the complexity of our everyday lives. As such, smart personal assistants such as Amazon’s Alexa or Apple’s Siri combine the comfort of intuitive natural language interaction with the utility of personalized and situation-dependent information and service provision. However, research on SPAs is becoming increasingly complex and opaque. To reduce complexity, this paper introduces a classification system for SPAs. Based on a systematic literature review, a cluster analysis reveals five SPA archetypes: Adaptive Voice (Vision) Assistants, Chatbot Assistants, Embodied Virtual Assistants, Passive Pervasive Assistants, and Natural Conversation Assistants. open access Knote, Robin Janson, Andreas Söllner, Matthias Leimeister, Jan Marco Honolulu, Hawaii doi:10.24251/HICSS.2019.245 Autonomer Agent Klassifikation Cluster-Analyse publishedVersion 2019-01 Wailea, Hawaii Proceedings of the 52rd Annual Hawaii International Conference on System Sciences Hawaii International Conference on System Sciences 2019 ISBN 978-0-9981331-2-6 2024-2033 false Hawaii International Conference on System Sciences 2019
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