Analyzer of the News Background Based on the Neural Network

The history of the news has a great impact on the high-volatile cryptomarket dynamics. News regarding hard forks, for example, can shift the price of a specific cryptocurrency by tens of percent.

The correct analysis of the news flow greatly improves the trader's professional performance. Furthermore, recent advances in the field of artificial intelligence make it possible to automate work every day with massive data sets that come from the media.

A variety of technologies and architectural methods are now used by advanced companies engaged in the field of machine learning to develop systems for automated text information processing.

We assume that it is most fitting to build neural networks based on LSTM-architecture. If there is a required number of nodes, long short-term memory makes calculations of any complexity.

Because of its high efficiency in tasks related to analysis and clustering of text arrays, this method was chosen.

The method based on this machine learning algorithm allows the input material to be submitted in a suitable format for review. The individual development that is tailored for training on crossing user choices is the basic implementation of the interaction and filling of nodes.

You can simulate a certain analog of human memory using this architecture.

Not only can this neural network discover banal patterns from word combinations, but it also allows the relationships between various news over time to be analyzed, which will improve its usefulness as a news analyzer a lot.