User behavior learning method based on PST in wireless network

A technology of wireless network and learning method, which is applied in the direction of specific mathematical model, wireless communication, data exchange network, etc. It can solve the problems of unable to meet the growth of business capacity, and achieve the effect of fast traversal speed, improved network performance, and good theoretical performance

Inactive Publication Date: 2013-10-02
NANJING UNIV OF POSTS & TELECOMM
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Simple expansion cannot meet the needs of business capacity growth, so active perception, analysis, decision-making and control of business is one of the fundamental ways to solve current network problems

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • User behavior learning method based on PST in wireless network
  • User behavior learning method based on PST in wireless network
  • User behavior learning method based on PST in wireless network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] Below in conjunction with accompanying drawing, the technical scheme of invention is described in detail:

[0041] The present invention proposes a PST-based user behavior learning algorithm, which divides business-based user behavior into four categories: no business (no business), conversational business (voice service, video conferencing), interactive business (web browsing , download), and streaming media services (video, audio), a single user can generate a 4-ary user behavior sequence within a period of time. The training behavior sequence is used to predict the behavior that may occur in the next time period, so as to determine the type of business, and then select the appropriate network resources to provide users with high-quality business. This solution combines the learning and training method of PST state tree and the prediction method based on variable length Markov model, which effectively improves the accuracy of user behavior prediction.

[0042] The pr...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a user behavior learning method based on a PST (Probabilistic Suffix Tree) in a wireless network. The method comprises the steps that a user behavior based on a business is divided into no business, a session business, an interaction business and a streaming media business according to different network QoS (Quality of Service) requirements of the business in the wireless network; a quaternary user behavior state sequence is generated; and an appropriate network resource can be selected for providing a high-quality service for a user according to a predicted business behavior by learning to construct the PST to train the user behavior sequence, and adopting the possible user behavior during a time period of a variable-length Markov model prediction. The method can improve the accuracy of user behavior prediction, is simple, and convenient to realize, and has a very good application prospect.

Description

technical field [0001] The invention relates to PST-based training and learning of user behavior in a wireless network and prediction based on a variable-length Markov model, and belongs to the technical field of wireless communication. Background technique [0002] The future ubiquitous network will show the characteristics of integration and intelligence, and environmental awareness is the premise and key to realize network integration and intelligence. Environmental awareness refers to extracting various resource information of complex networks, obtaining context information such as terminals, networks, services, and users through perception, and analyzing the above information for network decision-making, so as to improve network utilization and user experience quality the goal of. Environmental awareness can be divided into user awareness, service awareness, network awareness and terminal awareness. [0003] User awareness is actually user-centric context awareness in...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/00H04L12/24G06N7/00
Inventor 张晖陈娟杨龙祥朱洪波
Owner NANJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap