An improved SVM web page classification algorithm

Abstract

This study explored an indepth support vector machine(SVM) classification algorithm suitable for high-dimension computing. An improved SVM algorithm was proposed aiming at two kinds of classical kernel functions of support vector machine. The global kernel function and the local kernel function were weighted into a new mixed kernel function, and the genetic algorithm was used to optimize the function parameters. The improved algorithm avoided the limitation of a single kernel function, taking into account the generalization and learning abilities of the text classification algorithm. Simulation experiments of the collected web pages confirmed the effectiveness of improved SVM algorithm.