[Objective]To solve the problem of difficulty in accurately depicting the quality of micro, medium, and small enterprises (MSMEs), the comprehensive quality profiling technology of MSMEs based on deep learning is studied.

[Methods]A comprehensive quality profiling system of MSMEs in 5 dimensions including quality innovation ability, process quality control, product quality level, operational quality and risk, and financial quality are proposed, and the diversified profiling methods are designed for different data types of indicators. Focusing on the web text data of quality spot checks reports, user comments, etc., the comprehensive quality profiling construction technology of MSMEs based on deep learning is proposed.

[Results]The empirical results show that, in terms of F value, the recognition effect of the pre-trained Bert model for three types of quality entities is 4.66%, 1.99%, and 4.25% higher than the benchmark model respectively and the review classification model based on the pre-trained Word2Vec is 6.03% higher than the traditional TF-IDF model.

[Limitations] Limited by the availability of data, more dimensions of portraits related to enterprise quality need to be further optimized and improved.

[Conclusions] Deep learning technology expands the dimension and improves the accuracy of enterprise quality profiling, and provides technical support for service mode innovation of enterprise quality service organization.