Web Document Classification using Support Vector Machine

Accurate classification of web document is prime concern of search engines as web documents are scattered all over web and constantly evolving. The aim of this paper is to classify the web document which are related to freelance and remote job. The classification involves preprocessing, document representation, construction of SVM classifier. The performance evaluation of SVM is done using different set of training data. From the experiment we observed that SVM is performing well with evolved training set. Performance evaluation is done by selecting different kernel function and gamma parameter.