Semantic fuzzy recognition method based on real intention of a user

Abstract

The invention discloses a user real intention-based semantic fuzzy recognition method, which comprises the following steps of: carrying out feature extraction on a large amount of historical data withcorrect field classification through a Chinese word segmentation tool and a word frequency matrix to form a feature word list; performing word segmentation on the single request text data of the sameuser and a plurality of pieces of request text data in a preset time period to obtain a word segmentation list; respectively constructing membership functions for different fields, wherein the membership functions are used for performing fuzzy pattern recognition on request text data which fail to be classified; and respectively calculating membership degrees of the request text data failed in classification to different fields, and performing field classification on the request text data failed in classification according to a principle of a maximum membership degree. According to the method, fuzzy pattern recognition is carried out on the request text data failed in classification through the maximum membership degree principle for the user request text data failed in semantic analysis,so that domain classification is carried out, the classification accuracy is improved, and the semantic analysis accuracy is further improved.

Description

technical field [0001] The invention relates to the technical field of computer natural language processing, in particular to a semantic fuzzy identification method based on the user's real intention. Background technique [0002] With the development of information technology and the popularization of the concept of artificial intelligence, more and more customer services are developing in the direction of intelligence. People can interact with smart devices through simple voice input. Natural language processing is an important direction in the field of computer science and artificial intelligence. Research on natural language processing, speech semantic recognition and related technologies can help people interact with smart devices more conveniently and effectively, and then realize their true intentions. In the process of voice human-computer interaction, the common method is to convert the user's voice information into request text data first, then perform semantic ana...

AI Technical Summary

Problems solved by technology

[0003] At present, the main problem of semantic recognition is that, on the one hand, the voice signal error caused by the user’s speech speed, pitch, and dialect accent causes the request text data to be distorted, so subsequent processing cannot be performed; on the other hand, the semantic recognition The analysis is only for an independent sentence, without considering the context of the situation, and lacks an understanding of the user's true intentions

Due to the above defects, there are a large number of request texts that fail semantic parsing in semantic recognition at this stage. These text data are short in length, highly confusing, indistinct in features, and low in recognition rate

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