Personalized web page filtering method

Abstract

The invention relates to a web page filtering method which can be individually customized, which comprises steps: extracting the characteristics of a user example web page and a training web page base, excavating the attribute of a user interest class based on semi-supervised learning, conducting the characteristic extraction of the user interest class and the characteristic selection, and filtering the personalized web pages based on a Bayesian classifier. The invention provides a novel web page filtering frame driven by examples, the filtering demands of the users can be expressed through web page examples, the user examples can be any type web pages or multi-type composite web pages, and a web page filter in line with the individual demands of the user can be constructed by means of the semi-supervised learning, thereby overcoming the disadvantages of the limitation to single filtering or limited type web page, and unavailable realization of individual customization in a traditional web page filtering method. The method has the advantages of high accuracy, robustness and operation speed, and has excellent application prospects.