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Opportunities for Case-Based Reasoning in Personal Flow and Productivity Management

Part of the Lecture Notes in Computer Science book series (LNAI,volume 12311)

Abstract

Knowledge workers can benefit from tools to support them in performing deep, concentrated work. Research in biofeedback has shown success in training relaxation, but not in directly influencing task performance. One reason for this may be the difficulties users have in contextualizing biofeedback signals for different task situations. This presents an opportunity to leverage the strengths of case-based reasoning to select the feedback mechanism that will produce the best response. This paper describes initial research into the Adaptive Choice Case-Based Reasoning (ACCBR) system, that learns from and interacts with a user to assist them in achieving greater concentration and productivity.

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Correspondence to Thomas C. Eskridge .

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Eskridge, T.C., Weekes, T.R. (2020). Opportunities for Case-Based Reasoning in Personal Flow and Productivity Management. In: Watson, I., Weber, R. (eds) Case-Based Reasoning Research and Development. ICCBR 2020. Lecture Notes in Computer Science(), vol 12311. Springer, Cham. https://doi.org/10.1007/978-3-030-58342-2_23

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  • DOI: https://doi.org/10.1007/978-3-030-58342-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58341-5

  • Online ISBN: 978-3-030-58342-2

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