A Survey of Machine Reading Comprehension Methods

With the gradual maturity of deep learning technol-ogy, machine reading comprehension in natural language processing has become a popular research direction. Its research goal is to use computers to build models that enable computers to read articles, analyze semantics, and answer questions like humans. Due to the explosive growth of current text data, using models to quickly focus relevant information from text can save a lot of costs. Therefore, machine reading comprehension technology that can automatically process text has great research value. This paper summarizes the machine reading comprehension based on neural network in detail: first, the task definition and development process of machine reading comprehension are briefly introduced; secondly, the data sets and evaluation indicators of machine reading comprehension are introduced; then, the neural network of machine reading comprehension is introduced Model, including model architecture and some typical models; finally, the future development trend of machine reading comprehension is prospected.