Deep learning-based garbage text filtering method

Abstract

The invention discloses a deep learning-based garbage text filtering method. The method comprises the steps of filter character data at first, removing unnecessary symbols, spaces and modal particles,classifying according to different data types in the garbage text, marking and distinguishing character data and graph data without changing sequence and position of the two types of data, convertinggraph data into character data through a deep learning algorithm, wherein data conversion is integral to the deep learning method, comparing with forbidden words in a cloud server through the deep learning algorithm by combining original character data so as to obtain a garbage text, wherein text comparison represents important promotion of the deep learning method and can realize effective, deepinterception and prompt. The existing text filtering method cannot screen out the garbage text consisting both character data and graph data. The method solves the above problem, and uses the deep learning algorithm in garbage text processing, thereby improving screening accuracy.

Description

technical field [0001] The invention belongs to the technical field of big data processing, and more specifically, relates to a method for filtering garbage text based on deep learning. Background technique [0002] Text data is the most common type of semi-structured data in computer science. Many information in the real world needs to be expressed through text, and communication between users can also be realized through the exchange of text information. In this way, it is possible to generate junk text information that is useless to users. [0003] With the increasing enrichment of text data generation and processing methods in computer science and technology, coupled with the rapid development of data transmission speed, text information is not only generated by encoding types such as ASCⅡ, GBK and BIG5, but may also be enriched by means of graphic data. text information. Furthermore, junk text information may be hidden in graphic data, and character data and graphic d...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a spam text filtering method based on deep learning, thereby solving the problem that the existing spam text filtering method has a low ability to discriminate graphic data in the text and often cannot To effectively intercept or prompt technical problems

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