Analysis of Semantic Comprehension Algorithms of Natural Language Based on Robot’s Questions and Answers

Abstract

The deep learning has made a significant breakthrough and rapid development in the field of natural language processing under the background of big data. We analyzed deep learning algorithms based on natural language processing and its semantic comprehension, and studied the method of natural language semantic comprehension of robot's questions and answers that is suitable for commercial use occasion, by consulting and analyzing related works and literatures, we sorted out and analyzed the methods of existing deep learning algorithms in natural language processing and semantic comprehension, aimed to improve the accuracy of robots in recognizing users' core information and extracting users' true intentions from the theoretical research level. This paper summarized the natural language semantic comprehension algorithms and research progress suitable for robot's questions and answers around preprocessing technology, word sense disambiguation, semantic integrity analysis, etc. on this basis, through contrast tests and performance analysis, and laid the foundation for further scientific research.