Research on the Optimizing Method of Question Answering System in Natural Language Processing

Abstract

Natural language processing technology can not only enrich the functions of computers, but also fundamentally promote the development of artificial intelligence technology. Based on natural language processing technology, many useful systems for people's survival and life have been produced, such as the question-and-answer system described in this thesis. This system mainly uses natural language processing technology and information retrieval technology. Although it is based on text retrieval, it is quite different from traditional search engine. Traditional search engines point out that users need to input a series of keyword combinations, and users can only get a variety of related websites, but also rely on their own discrimination ability to select useful information. However, the question answering system can allow users to input a question in the form of natural language. Finally, according to the search and judgment, the system can get a short and accurate answer to the user, which greatly improves the convenience of people's production and life. This thesis mainly elaborates the content of question answering system of natural language processing and analyses how to optimize it.