Research And Development Of Agricultural Production Intelligent Question Answering System Based On Deep Learning

Agriculture is China's primary industry and plays a vital role in economic development and social stability.For farmers,agricultural production is the main source of economic resources.Therefore,it is very important to quickly solve the production and technical problems encountered in agricultural production.With the development of information technology and the popularity of the Internet,mobile phones have become an indispensable part of our lives.Agricultural workers often use the Internet to search for issues related to agricultural production,hoping to get the corresponding solutions and knowledge.However,the network will return a large number of collections of valid and invalid information data to the user,which must be manually filtered for secondary screening,so it is very troublesome to get answers.It is extremely urgent to develop an intelligent question and answer system for agricultural production to help relevant personnel solve technical problems related to agricultural production.In recent years,the development of question-and-answer technology for specific fields,from the initial simple word matching technology to the current deep semantics and semantic matching technology,to build a high-precision,convenient and fast intelligent question answering system for agricultural production.Provided the possibility.This paper will comprehensively consider the importance of agricultural production and the convenience of solving agricultural production problems,make full use of the convenience of WeChat small program,and we design and implement a deep learning-based agricultural production question and answer system.The system first constructs a model based on LSTM semantic similarity calculation,and encapsulates the model.Then,based on the MVC structure,the MySQL and MongoDB databases are used to store data,and the Sybase Flask Web framework is used to build the background system.Use the WeChat web developer tool to build the front end and complete the interaction of the corresponding functional modules.