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Artificial Social Intelligence: Hotel Rate Prediction

  • James J. LeeEmail author
  • Misuk Lee
Conference paper
  • 26 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1130)

Abstract

Artificial Intelligence has enabled new possibilities in today’s business domain from operational efficiency to smart decision making and even innovative product/service design. Still there are plenty of grey areas where human modelers are struggling to create optimal machine learning scenarios. This research is the first attempt to build machine level structuration where the human modelers’ continuous commitment to enhance machine learning models can be eliminated. In Artificial Social Intelligence Framework, those requirements are replaced at the machine level by adopting cloud native computing foundation (CNCF) with continuous integration and development. The suggested machine level structuration is demonstrated with hotel rate predictions.

Keywords

Artificial Social Intelligence Cloud native Hotel rate prediction Structuration 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Seattle UniversitySeattleUSA

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