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Improving Effectiveness of a Coaching System Through Preference Learning

Published: 29 June 2021 Publication History

Abstract

The paper describes an approach for indirect assessment and use of user preferences in an unobtrusive sensor-based coaching system with the aim of improving coaching effectiveness. The preference assessments are used to adapt the reasoning components of the coaching system in a way to better align with the preferences of its users. User preferences are learned based on data that describes user feedback as reported for different coaching messages that were received by the users. The preferences are not learned directly, but are assessed through a proxy – classifications or probabilities of positive feedback as assigned by a predictive machine learned model of user feedback. A brief description of the coaching setting is provided in the paper, before the approach for preference assessment is described and illustrated on a real-world example obtained during the testing of the coaching system with elderly users.

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  • (2022)Improving Effectiveness of a Coaching System through Preference LearningTechnologies10.3390/technologies1001002410:1(24)Online publication date: 31-Jan-2022

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PETRA '21: Proceedings of the 14th PErvasive Technologies Related to Assistive Environments Conference
June 2021
593 pages
ISBN:9781450387927
DOI:10.1145/3453892
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 29 June 2021

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  1. Machine Learning
  2. Preference Learning
  3. User Centered Design

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  • (2022)Improving Effectiveness of a Coaching System through Preference LearningTechnologies10.3390/technologies1001002410:1(24)Online publication date: 31-Jan-2022

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