Network Search Based on Weighted Vector Space Model
基于加权向量空间模型的网络搜索*

In order to train and categorize the articles more efficiently, which are obtained from Internet, this paper gives a new model of a classifier. This model applies the weighted factors of keywords on traditional Vector Space Model(VSM) and optimizes the characteristic vectors of articles when they have been trained. It can repair the weighted values of keywords and make the selection of the threshold value more convenient. The tests prove that this classifier which can categorize articles reasonably and more precisely also has the learning capacity.