Junk short message detection method, terminal and computer readable storage medium

A technology for spam text messages and detection methods, applied in neural learning methods, unstructured text data retrieval, biological neural network models, etc., can solve problems such as low detection accuracy of Chinese spam text messages

Inactive Publication Date: 2019-07-16
CHINA MOBILE COMM LTD RES INST +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to provide a spam message detection method, a terminal and a comput...

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  • Junk short message detection method, terminal and computer readable storage medium
  • Junk short message detection method, terminal and computer readable storage medium
  • Junk short message detection method, terminal and computer readable storage medium

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Embodiment Construction

[0116] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0117] Aiming at the problem of low detection accuracy of Chinese spam text messages in the prior art, the present invention provides a spam text message detection method, such as figure 1 shown, including:

[0118] Step 11: Preprocessing the received short message to obtain a digital code string;

[0119] Step 12: Obtain the target matrix according to the digital code string;

[0120] Step 13: According to the target matrix, confirm whether the received short message is a spam short message.

[0121] The spam short message detection method provided by the embodiment of the present invention obtains a digital code string by preprocessing the received short message; obtains a target matrix according to the digital code string; and confirms whether the r...

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Abstract

The invention provides a junk short message detection method, a terminal and a computer readable storage medium, and the junk short message detection method comprises the steps: carrying out the preprocessing of a received short message, and obtaining a digital code string; obtaining a target matrix according to the digital coding string; and determining whether the received short message is a junk short message or not according to the target matrix. The method comprises the following steps of: preprocessing a received short message to obtain a digital coding string; obtaining a target matrixaccording to the digital coding string; determining whether the received short message is a junk short message or not according to the target matrix; characteristics are automatically extracted, manual intervention is not needed, the detection precision is greatly improved, and the problem that in the prior art, the Chinese spam short message detection precision is low is well solved.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a spam short message detection method, a terminal and a computer-readable storage medium. Background technique [0002] The current Chinese spam detection algorithm adopts the form of cascading multi-layer determinators. The determinators of each layer are responsible for processing some types of spam messages, and pass other types that cannot be processed by this layer to the next layer for processing. The cascaded decision devices at each level include five parts: fingerprint decision, prior model decision, big data cluster analysis, text classifier, and policy marking. Among them, the establishment of the determiner of each layer is based on the professional knowledge accumulated by business personnel, extracting features, and using machine learning algorithms on the basis of feature engineering to conduct supervised learning-based training methods to train the ...

Claims

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Application Information

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IPC IPC(8): G06F16/35G06N3/04G06N3/08H04W4/14
CPCG06N3/08H04W4/14G06F16/35G06N3/045
Inventor 孙宝华林景贤李俭
Owner CHINA MOBILE COMM LTD RES INST
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