Internet information risk prompting method and system

Abstract

The invention provides an internet information risk prompting method and system. The internet information risk prompting method comprises the steps that internet information serves as original text data, word segmentation is conducted on the original text data, words are converted into digital identifiers, and segmented word arrays consisting of the digital identifiers are formed; according to theassociation relation of corresponding words of the digital identifiers in the segmented word arrays and context, the segmented word arrays are mapped into corresponding word vector sequences; classified identification is conducted on the word vector sequences through a neural network model to obtain classification result data; risk analysis is conducted on the classification result data, and riskprompts are sent according to risk analysis results. The internet information risk prompting method can understand human languages in the mode of thinking closer to human thinking, and a variety of information can be quickly and intelligently identified. Thus, when much information is processed, workers can be replaced to organize huge complicated service texts and rapidly identify risk event information, and lots of labor and time are saved.

Description

technical field [0001] The invention relates to the field of Internet information processing, in particular to an Internet information risk warning method and system. Background technique [0002] In the context of the era of big data, the mass information scattered on the Internet by enterprises contains a lot of valuable but unused information. If we can identify risk-related events in time and dig out potential risk characteristics, we will be able to Timely, comprehensive and intuitive grasp of customer risks, greatly improving the ability of enterprises to identify and reveal risks. [0003] Identifying risk themes implicit in event information is essentially a text classification task. In the traditional method, the ontology model based on the rule is mainly used to classify the text; that is, an ontology is established for each classification, and the characteristic vocabulary or business rules are defined by experts as elements. Although existing technologies can b...

AI Technical Summary

Problems solved by technology

[0007] Therefore, for Internet information risk warnings, when dealing with massive complex semantic texts, existing technologies have the following deficiencies: the recognition efficiency is low, and only text content with simple semantics can be recognized. The text recognition error rate of complex language expressions such as deliberate denial is high. If it is replaced by manual screening, it will consume a lot of manpower and time

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