Banca de DEFESA: Michael Rodrigues da Silva

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : Michael Rodrigues da Silva
DATE: 01/08/2023
TIME: 14:00
LOCAL: remoto
TITLE:

Reactive Cognitive Architecture based on microservices and micro frontends to improve the user experience in internet banking through Adaptive Interfaces

KEY WORDS:

Reactive Cognitive Architecture based on microservices and micro frontends to improve the user experience in internet banking through Adaptive Interfaces

PAGES: 87
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Engenharia de Software
SUMMARY:

Advances in communication and computing technologies have boosted the use of the internet, affecting the life of society and playing an important role in business. The banking industry has followed this evolution, offering essential services through the internet to millions of customers. In addition, competition between banks that offer services through the internet has grown more and more. In this scenario, it is observed that the User Experience (UX) is an important factor in the perception of quality by the customers of these institutions, even influencing the choice between one bank and another. As the software architecture is an important element that affects usability, it is essential to ensure that usability and user experience criteria are supported when planning this architecture. Therefore, this work proposes an architecture for banking systems based on concepts of reactive systems, providing for integration with services and heterogeneous data sources to improve the UX, with an interface that adapts to the user based on their behavior and characteristics. For this reason, adaptive interfaces tend to offer a better user expe- rience, as they seek to adapt to the needs and desires of users. There are several ways to render adaptive applications, this work follows the micro-frontends model, as it gener- ates smaller, more cohesive and sustainable code bases, making it possible to work with autonomous teams and different technologies. These characteristics are important, espe- cially for larger corporations, which support larger groups of professionals and teams. The architecture proposed by this work uses the Reinforcement Learning algorithm, added to the Monte Carlo Tree Search (MCTS) algorithm and the Deep Learning technique, to create adaptive applications. Finally, a robust backend system has to be developed to extract, store and process user data, so the microservices’ architecture was adopted, which allows applications to be formed by small, cohesive and independent services.

COMMITTEE MEMBERS:
Presidente - 2325777 - LETICIA LOPES LEITE
Interno - 1558082 - ANDRE LUIZ PERON MARTINS LANNA
Interno - 1072256 - EDISON ISHIKAWA
Externa à Instituição - MÁRCIA CRISTINA MORAES - UCLA