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Mobile internet service quality prediction method based on feature selection

A mobile Internet, service quality technology, applied in the field of mobile Internet applications

Inactive Publication Date: 2019-07-23
BEIJING UNION UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The customer service department only discovers the problem of service experience when it receives complaints from users, and then coordinates with the network operation and maintenance and optimization department to troubleshoot and solve the problem, which is often very passive

Method used

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  • Mobile internet service quality prediction method based on feature selection
  • Mobile internet service quality prediction method based on feature selection
  • Mobile internet service quality prediction method based on feature selection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0117] Take the webpage browsing service under the LTE network as an example. The specific method steps are as follows:

[0118] Step S1: Construct a training sample set

[0119] It is known that under the local mobile network of a certain city, when a user uses a web browsing business app (such as UCweb, QQ browser, etc.) When a certain webpage is accessed, the service perception samples of webpage browsing at this time are obtained through the data collection App deployed on the user terminal, and these samples constitute the "service perception sample set" D′={(x′ i ,y′ i ), i=1~M'}, including a total of M'=30000 samples. Each sample contains P=15 feature items: feature 1, feature 2, ..., feature P, denoted as: x'={x' 1 , x′ 2 ,...,x′ P}; and T=4 mark items: mark 1, mark 2, ..., mark T, recorded as: Y'={y' 1 ,...,y′ T}. For web browsing services, it is: DNS resolution delay, TCP connection delay, GET request delay, and receiving response delay.

[0120] Among them...

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Abstract

The invention discloses a mobile internet service quality prediction method based on feature selection. The method comprises the following implementation processes of S1, constructing a training sample set; S2, calculating a feature weight; S3, constructing a k-nearest neighbor sample set of the training samples; S4, calculating a prior probability and a normalized frequency matrix; s5, constructing a k-nearest neighbor sample set of an unknown sample; s6, calculating the same mark statistics of the unknown sample; s7, calculating the likelihood probability of an unknown sample; s8, estimatinga mark value of an unknown sample. According to mass user service perception historical data (the quality of the service perception indexes under different scenes), prediction and early warning are carried out on the quality of the service experience of the user under the specific scene, service experience problems can be found as early as possible, relevant measures can be taken in time for improvement, and the complaint rate and the off-network rate are effectively reduced.

Description

technical field [0001] The invention relates to a method for predicting mobile Internet service quality, in particular to a method for predicting mobile Internet service quality based on feature selection, and belongs to the technical field of mobile Internet applications. Background technique [0002] When mobile network users use OTT services (such as web browsing, video playback, etc.), the quality of their service experience can generally be evaluated by KQI (Key Quality Indicator) indicators, such as webpage opening delay, download rate, etc. The quality of this experience is affected by many factors, including the quality of the terminal, the quality of the mobile network where the service is used, the quality of the APP, the bandwidth and load of the SP website server cluster, and so on. [0003] As the transmission channel provider of various services and the key link of service experience assurance, telecom operators need to ensure the user's service experience as m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08
CPCH04L67/535
Inventor 李克谢苏陈明
Owner BEIJING UNION UNIVERSITY
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