In a summary please help me to understand the material, and consideration of which benefits of BI and Analytics in this reading on User Interface Adaptation based on a Business Rules Management System and Machine Learning.

In ubiquitous computing environments, computers are embedded into everyday lives to provide information anywhere and at any time. Pervasive computing assists us in our everyday activities, operating invisibly in the background, regardless of our location or devices. Therefore, ubiquitous computing requires discovering new Human-Computer Interaction methods helping users to easily interact with ubiquitous systems whatever is the perceived context situation. However, designing context-aware applications that are able to adapt to context instability is a recurring problem that requires special attention from researchers in the HCI community. On the one hand, it is not trivial for a designer to specify how UIs should adapt, and on the other hand it is very hard to predict the context of use changes and accordingly to construct adaptive UIs that match users expectations. In this paper, we present a Model Driving Engineering (MDE) technique to design UIs that automatically adapt to the perceived context situation while the designer and eventually the end user still have full control over the adaptation during runtime. This technique is supported by a conceptual framework and a graphical tool that lower the threshold for designers as well as developers to design adaptive user interfaces, modelize context situations, edit adaptation rules and manage the adaptation process.

Emerging ubiquitous environments deliver products and services that are more and more sophisticated creating competitive challenges for computer engineers particularly the Human-Computer Interaction (HCI) community. Welldesigned User Interfaces (UIs) could fail to satisfy end-users if they do not cover the unpredictable dynamic variation of the context of use. UIs should be accessed through several devices such as smart phones, notebooks and tablets and used by people with different skills and abilities. This implies the necessity of qualifying UIs with flexibility and adaptability to increase their level of accessibility and accommodate the context requirements. During the last decade, several successful solutions have been proposed to deal with this issue. Some research studies like Zouhaier et al (2015), Peissner et al (2012) and Min et al (2013), address the problem at the design-time and aim to generate multiple variants of a UI for multiple target devices and users. Chen et al (2014), Criado et al (2015) and Mezhoudi et al (2015) focus on a fully dynamic approach where the adaptation behavior is performed at runtime. However, most of these solutions neither end-user nor designer takes part in the adaptation process in order to select relevant adaptation rule or strategy to be performed. In our work, we adopt a Model Driven Development approach to generate Final User Interface (FUI) adapted to a specific contexts situation. In addition, the adaptation specifications are integrated in the generation process of the Cameleon Reference framework (CRF), proposed by Calvary et al (2003), in order to ensure that UI consistency is preserved even when making changes at any level representation and regenerating the interface. We also take into account that the designer should be a full partner throughout the process.