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Dynamically predictable data flow detection and classification method and device

A data flow and dynamic prediction technology, applied in structured data retrieval, database models, relational databases, etc., can solve problems such as intelligent identification and refined classification of difficult multi-source data flows, and limited business operation scenarios

Active Publication Date: 2020-11-13
上海飞旗网络技术股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In traditional solutions, it is usually only possible to intelligently identify and finely classify single-source data streams, and it is difficult to intelligently identify and finely classify multi-source data streams, thus limiting business operation scenarios

Method used

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  • Dynamically predictable data flow detection and classification method and device
  • Dynamically predictable data flow detection and classification method and device
  • Dynamically predictable data flow detection and classification method and device

Examples

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Embodiment Construction

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the appended The figures are only for the purpose of illustration and description, and are not used to limit the protection scope of the present application.

[0044] figure 1 A schematic diagram of an application scenario of the data traffic detection and classification system 10 provided by the embodiment of the present application is shown. In this embodiment, the data traffic detection and classification system 10 may include a server 100 and a user terminal 200 communicatively connected to the server 100 .

[0045] The user terminal 200 may include, but is not limited to, a mobile device, a tablet computer, a laptop computer...

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Abstract

Embodiments of the present application provide a dynamically predictable data flow detection and classification method and device, which obtain training samples by analyzing multi-source heterogeneous big data. Then, split the training samples according to the label type, and calculate the flow session feature vector and the regression model prediction vector of each split training sample. Through the hybrid deep learning of stream session feature vectors and regression model prediction vectors, the data characteristics of multi-source heterogeneous data can be considered, and multi-source heterogeneous data streams can be intelligently identified and finely classified, providing big data services and application aggregation. Capability support to realize the deep mining of the value of big data.

Description

technical field [0001] The present application relates to the technical field of data flow detection and classification, and in particular, to a dynamically predictable data flow detection and classification method and device. Background technique [0002] At present, real-time analysis application scenarios for multi-source heterogeneous massive data have become more and more common. How to intelligently identify and finely classify unknown multi-source data streams, so as to provide real-time big data analysis and processing for subsequent business operations, is a major problem in this field. In traditional solutions, it is usually only possible to intelligently identify and finely classify single-source data streams, but it is difficult to intelligently identify and finely classify multi-source data streams, thus limiting business operation scenarios. Contents of the invention [0003] In view of this, the purpose of this application is to provide a dynamically predic...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/28G06K9/62
CPCG06F16/285G06F18/241
Inventor 杨贻宏
Owner 上海飞旗网络技术股份有限公司
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