  The efficiency of natural language processing has improved dramatically with
the advent of machine learning models, particularly neural network-based
solutions. However, some tasks are still challenging, especially when
considering specific domains. In this paper, we present a cloud-based system
that can extract insights from customer reviews using machine learning methods
integrated into a pipeline. For topic modeling, our composite model uses
transformer-based neural networks designed for natural language processing,
vector embedding-based keyword extraction, and clustering. The elements of our
model have been integrated and further developed to meet better the
requirements of efficient information extraction, topic modeling of the
extracted information, and user needs. Furthermore, our system can achieve
better results than this task's existing topic modeling and keyword extraction
solutions. Our approach is validated and compared with other state-of-the-art
methods using publicly available datasets for benchmarking.
