Sara Adib

Sara Adib

MSc

Start: Sep. 2017
Finish: Jun. 2020
Thesis Title: A Framework for Model-Driven Development of Context-Aware Recommender Mobile Applications
Supervisor: Dr. Bahman Zamani
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Thesis Abstract:
In recent years, mobile recommender ‎systems‎ such as tourism recommender systems have been increasingly used by users. Mobile recommender can enhance user experience by using contextual information, which can be easily captured via mobile sensors. Context-Aware Recommender Systems (CARS) are systems that make use of user preferences and contextual Information to achieve customer satisfaction and improve the accuracy of recommendations.‎
Developing context-aware applications, particularly for a novice designer, is a challenging task due to the complexity of such applications. To overcome this complexity, the use of modern software engineering approaches, such as model-driven development, may help.‏‏ ‎Therefore, ‎‎‎this ‎thesis‎ proposes a model-driven framework for the automatic generation of context-aware mobile recommender systems. Due to the fact that the domain of context-aware recommender applications is very diverse and in model-driven approaches, it is desired to work on more specific domains to get more accurate code, the domain of this ‎thesis is limited to tourism‎. Besides the technical discussion, we limit our domain to tourism, because tourism is one of the leading domains in mobile applications especially in recommender systems.‎‎
Our framework, called ATCARS, consists of four components: a domain-specific modeling language, a graphical editor for modeling by this language, transformation code, and a platform in the Android studio environment. The modeling editor enables a designer to model a context-aware recommender application and then validates the model against the predefined constraints. After designing and validating the model, executable Android code is automatically generated from the ‎code. ‎Finally, by transferring the generated code to the developed platform and running the program, the production process of the application is completed. To evaluate the proposed framework, two context-aware recommender mobile applications ‎‎‏‎that ‎are ‎combined ‎in ‎one ‎app ‎called ‎”ARAS”‎ in the tourism domain have been developed automatically. Besides, we design a questionnaire and invite experts in the field of Android programming and model-driven to development To perform the evaluation process based on the criteria of usability, performance, and satisfaction. The evaluation results show 94\% ‎of app code is generated ‎automatically. ‎T‎his framework reduces development time and speeds up the development process based on the questionnaire results. To perform the evaluation process based on the criteria of usability, performance, and satisfaction.