NLP based artificial intelligence method for online semantic recognition of short and long text

Abstract

The current semantic recognition methods for long and short texts have low recognition accuracy and slow recognition speed for texts with obvious length differences, which can not accurately identify the deep semantics contained in the texts and restrict the development of text data. To solve this problem, based on the traditional text semantic recognition method, the natural language processing (NLP) artificial intelligence principle is introduced, and a new design of long and short text semantic recognition method is proposed. Extract the semantic features of the original text, and use the frequency method to process the lexical features in the text by weighting. Then, obtain the feature weights of the long and short texts and use the NLP artificial intelligence method to distinguish the unknown texts and identify the semantics of the long and short texts online. The experimental analysis shows that the accuracy of the semantic recognition methods proposed in this paper is more than 96. 87%. The accuracy is higher. The recall is less than 35. 27%. The recall is lower and the recognition advantage is significant compared with the traditional methods.