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How to Cope with Change? Preserving Validity of Predictive Services over Time

Baier, Lucas; Kühl, Niklas ORCID iD icon; Satzger, Gerhard

Abstract (englisch):

Companies more and more rely on predictive services which are constantly monitoring and analyzing the available data streams for better service offerings. However, sudden or incremental changes in those streams are a challenge for the validity and proper functionality of the predictive service over time. We develop a framework which allows to characterize and differentiate predictive services with regard to their ongoing validity. Furthermore, this work proposes a research agenda of worthwhile research topics to improve the long-term validity of predictive services. In our work, we especially focus on different scenarios of true label availability for predictive services as well as the integration of expert knowledge. With these insights at hand, we lay an important foundation for future research in the field of valid predictive services.

Verlagsausgabe §
DOI: 10.5445/IR/1000085769
Veröffentlicht am 12.02.2019
Cover der Publikation
Zugehörige Institution(en) am KIT Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2019
Sprache Englisch
Identifikator ISBN: 978-0-9981331-2-6
KITopen-ID: 1000085769
Erschienen in Hawaii International Conference on System Sciences (HICSS-52), Grand Wailea, Maui, Hawaii, Januar 8-11, 2019
Verlag University of Hawai'i at Manoa / AIS
Seiten 1085-1094
Vorab online veröffentlicht am 12.09.2018
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