Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Help Me Learn! Architecture and Strategies to Combine Recommendations and Active Learning in Manufacturing

Version 1 : Received: 4 October 2021 / Approved: 5 October 2021 / Online: 5 October 2021 (15:23:46 CEST)

A peer-reviewed article of this Preprint also exists.

Zajec, P.; Rožanec, J.M.; Trajkova, E.; Novalija, I.; Kenda, K.; Fortuna, B.; Mladenić, D. Help Me Learn! Architecture and Strategies to Combine Recommendations and Active Learning in Manufacturing. Information 2021, 12, 473. Zajec, P.; Rožanec, J.M.; Trajkova, E.; Novalija, I.; Kenda, K.; Fortuna, B.; Mladenić, D. Help Me Learn! Architecture and Strategies to Combine Recommendations and Active Learning in Manufacturing. Information 2021, 12, 473.

Journal reference: Information 2021, 12, 473
DOI: 10.3390/info12110473

Abstract

This research work describes an architecture for building a system that guide a user from a forecast generated by a machine learning model through a sequence of decision-making steps. The system is demonstrated in manufacturing demand forecasting use case and can be extended to other domains. In addition, the system provides means for knowledge acquisition by gathering data from users. Finally, it implements an active learning component and compares multiple strategies to recommend media news to the user. Such media news aims to provide additional context to demand forecasts and enhance judgment on decision-making.

Keywords

artificial intelligence; machine learning; active learning; knowledge acquisition; explainable artificial intelligence; manufacturing; demand forecasting; smart assistant

Subject

MATHEMATICS & COMPUTER SCIENCE, Artificial Intelligence & Robotics

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