摘要
The booming growth of the Internet provides us a great deal of information resource. In this paper, we create a text filtering model based on VSM. In this model,Web text mming is an efficient technique,which discoveres valuable and potential knowledge from those unstructured texts. In this paper,we use VSM as the description of Web text and give a feature subset algorithm which is based on the Genetic Algorthm. This algorithm can greatly improve the efficiency of dealing with Web texts and give much better way to classify and cluster the texts. Our experiments show that this method is active well in feature dimension reduction.
The booming growth of the Internet provides us a great deal of information resource. In this paper, we create a text filtering model based on VSM. In this model, Web text mining is an efficient technique,which discoveres valuable and potential knowledge from those unstructured texts. In this paper, we use VSM as the description of Web text and give a feature subset algorithm which is based on the Genetic Algorthm. This algorithm can greatly improve the efficiency of dealing with Web texts and give much better way to classify and cluster the texts. Our experiments show that this method is active well in feature dimension reduction.
出处
《计算机科学》
CSCD
北大核心
2001年第12期55-58,共4页
Computer Science
基金
天津自然科学基金(003700111)和(993600811)
