UI Personalization using Face Recognition and Machine Learning

Nowadays, the industry is running on the assumption that a single user interface (UI) can effectively engage a diverse group of users. However, it is not effectively implemented on several UI platforms which often leads to dissatisfaction among various user groups. Moreover, the majority of the users belong to a non-technological background with varying levels of understanding and comfortability with modern technology. Thus, a dynamically customized UI “tailormade” for front-end users' needs is a necessity. The presented exposition introduces a methodology to generate a personalized user interface using the age, gender and browser history of the user. It is processed using face recognition and machine learning techniques. Further, the concept of Fuzzy Logics is used to choose which websites the user might want to be personalized. The data for the generation of personalized UI is collected passively. Thus solving the issue of the passive response of the customer in customization and feedback features.

Keywords: User Interface, Customization, Machine Learning, Face Recognition, Fuzzy Logics

Suggested Citation: Suggested Citation

Garg, Apoorv and Dixit, Deepanshi and Khanna, Ashish and Doss, Srinath, UI Personalization using Face Recognition and Machine Learning (April 15, 2020). Proceedings of the International Conference on Innovative Computing & Communications (ICICC) 2020, Available at SSRN: https://ssrn.com/abstract=3576404 or http://dx.doi.org/10.2139/ssrn.3576404