Neural-network-based self-learning semantic detection method and system

A neural network and detection method technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of low success rate, achieve the effect of strengthening network information processing and identification, and has a wide range of applications

Inactive Publication Date: 2014-06-11
INST OF ACOUSTICS CHINESE ACAD OF SCI +1
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AI Technical Summary

Problems solved by technology

From the perspective of system composition, the existing discriminant system basically only has a word segmentation module and a discriminant module. It perf

Method used

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  • Neural-network-based self-learning semantic detection method and system
  • Neural-network-based self-learning semantic detection method and system
  • Neural-network-based self-learning semantic detection method and system

Examples

Experimental program
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Embodiment

[0053] Firstly, establish the structure of the overall information of the network by collecting data such as file names and file name hash values, and store them in database tables; The interrelationship among them is used as a communication medium, based on the Naive Bayesian algorithm for learning and classifying texts, the probability item of each word segmentation is calculated, so that the system can truly become a self-learning method; finally, the probability item of the word segmentation is used Make good and bad judgments on the file name, and get conclusions such as the attributes of the file name, so that the system truly has the ability of emotion recognition. refer to figure 1 , the detailed process is given below.

[0054] The first step: collect network information and store and organize the information into the database to structure the network information. The information is divided into two parts: system input information and system output information.

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Abstract

The invention discloses a neural-network-based self-learning semantic detection method and system. The method includes the steps: 101, a dictionary base is imported to segment filenames to be recognized so as to obtain keywords in the filenames, and a probability item of each keyword is calculated on the basis of a Bayesian algorithm; the probability items are analyzed and acquired on the basis of judgment results of good or bad filenames; 102, a product of multiplying a product of probabilities of all keywords occurring in good semantic string names and prior probabilities of the good semantic string names is obtained; a product of multiplying a product of probabilities of all keywords occurring in bad semantic string names and prior probabilities of bad semantic string names is obtained; 103, the two products are compared; if the product item of the good semantic string is larger than that of the bad semantic strings, the strings are determined as to have good semantics; if not, the strings are determined to have bad semantics; judgment results are stored in a storage medium.

Description

technical field [0001] The invention belongs to the field of network information processing and analysis, in particular to the field of automatic determination of the nature and tendency of text information content, and in particular to a neural network-based self-learning semantic detection method and system. Background technique [0002] The automatic processing and analysis technology of network information is an important part of realizing the analysis, detection and management of network content, and it is of great significance to the construction of network content processing and security system. [0003] Due to the continuous development of network technology and the continuous improvement of bandwidth provided by operators, users can easily access and download various information on the network. Information dissemination provides new convenience. In recent years, the dissemination of harmful information such as obscenity, pornography and reactionary information is p...

Claims

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Application Information

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IPC IPC(8): G06F17/27
Inventor 苏青苗光胜牛温佳唐晖慈松谭红艳
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI
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