A Web Page Access Prediction Method Based on K-Order Mixed Markov Model

A technology of page access and prediction method, which is applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve the problems of users losing information

Inactive Publication Date: 2011-11-30
NANJING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Users can easily get lost in the ocean of information

Method used

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  • A Web Page Access Prediction Method Based on K-Order Mixed Markov Model
  • A Web Page Access Prediction Method Based on K-Order Mixed Markov Model
  • A Web Page Access Prediction Method Based on K-Order Mixed Markov Model

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Embodiment Construction

[0039] figure 1 Shown is the overall technical framework of the Web page access prediction method. It can be seen that the input of this method is the historical log records of the Web server and the Web pages recently visited by the target user. The output of the method is a collection of recommended or prefetched web pages for the target user. The technical framework is divided into 5 modules: organize web page access logs and identify users; identify user sessions and build a web log database; select and organize log data according to prediction targets; train k-order hybrid Markov models; finally predict based on target user operations Next visit the page.

[0040] Web servers and their applications will continuously record user access log data during their work, and different web servers have slightly different log recording methods and data formats. Under normal circumstances, for each HTTP request of the user (or other protocols such as FTP, the method of the present ...

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Abstract

The invention discloses a Web page access forecasting method based on a k-order hybrid Markov model, and the method comprises the following steps of: firstly, gathering and handling Web server access log data, identifying a client and users and eliminating insignificant access data; then identifying user sessions to construct a Web log database; select log data from the database according to forecasting targets, and organizing (k+1) tuples by taking a session as a unit, wherein the (k+1) tuples are used for training the k-order hybrid Markov model; learning and calibrating a parameter set of the k-order hybrid Markov model by using an expectation-maximization algorithm; and identifying sessions according to page access operations of target users and applying the model for forecasting Web pages to be accessed by the users at the next step. The method provided by the invention can be used for recommending pages needed to be accessed by the users so as to reduce the delay of page access and optimize user experience; and in addition, from the point of a Web server, the organizational structure of the Web pages can be improved, the result sequence of a search engine is guided, and the page cache mechanism can be improved, thereby enhancing the quality of service.

Description

technical field [0001] The present invention relates to a personalized prediction technology for Web page access, especially for the situation that Web server information is becoming larger and more complex in the Internet age, and the number of user visits is increasing; it is necessary to determine the page that the user may visit in the next step according to the user's access characteristics , to help users find the information they need faster and better; at the same time, it assists the web server to pre-cache the pages that users need, improves the page link structure, and thus improves the server access efficiency. Background technique [0002] With the rapid development of the Internet, the World Wide Web (WWW) has become a worldwide hypermedia information acquisition platform. People rely more and more on the Web to obtain various information, and browsing the Web has become a part of people's daily life. . A complete web application includes web server, client br...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 顾庆任颖新汤九斌陈道蓄
Owner NANJING UNIV
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