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Service-Oriented Cognitive Analytics for Smart Service Systems: A Research Agenda

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Title:Service-Oriented Cognitive Analytics for Smart Service Systems: A Research Agenda
Authors:Hirt, Robin
Kühl, Niklas
Schmitz, Björn
Satzger, Gerhard
Keywords:Smart Service Systems: Analytic, Cognition and Innovation
analytics framework, cross-entity learning, cognitive learning, research agenda, smart service systems
Date Issued:03 Jan 2018
Abstract:The development of analytical solutions for smart services systems relies on data. Typically, this data is distributed across various entities of the system. Cognitive learning allows to find patterns and to make predictions across these distributed data sources, yet its potential is not fully explored. Challenges that impede a cross-entity data analysis concern organizational challenges (e.g., confidentiality), algorithmic challenges (e.g., robustness) as well as technical challenges (e.g., data processing). So far, there is no comprehensive approach to build cognitive analytics solutions, if data is distributed across different entities of a smart service system. This work proposes a research agenda for the development of a service-oriented cognitive analytics framework. The analytics framework uses a centralized cognitive aggregation model to combine predictions being made by each entity of the service system. Based on this research agenda, we plan to develop and evaluate the cognitive analytics framework in future research.
Pages/Duration:8 pages
URI/DOI:http://hdl.handle.net/10125/50090
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.203
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Smart Service Systems: Analytic, Cognition and Innovation


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