An investigation of information intelligence retrieval model in local searching systems

The process of building and learning neural networks requires considerable computational effort. Fortunately, nowadays there are many various systems with high computing power. Development of systems, algorithms, methods and their applications in machine learning has become a promising direction in science. The work is devoted to the investigation of information retrieval problems and the main problems associated with this task, constructing an overfit-safe neural network model for improving the local searching system quality on 49 % using machine learning algorithms.