The emergence of explainability of intelligent systems: Delivering explainable and personalized recommendations for energy efficiency

The recent advances in artificial intelligence namely in machine learning and deep learning, have boosted the performance of intelligent systems in several ways. This gave rise to human expectations, but also created the need for a deeper understanding of how intelligent systems think and decide. Th...

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Veröffentlicht in:	International journal of intelligent systems 2021-02, Vol.36 (2), p.656-680
Hauptverfasser:	Sardianos, Christos, Varlamis, Iraklis, Chronis, Christos, Dimitrakopoulos, George, Alsalemi, Abdullah, Himeur, Yassine, Bensaali, Faycal, Amira, Abbes
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Customization Decision making Energy efficiency explainable recommendation system Impact analysis Intelligent systems Internet of things Machine learning recommendation systems Recommender systems rule‐based recommendation System effectiveness user habits
Online-Zugang:	Volltext
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