Web text clustering algorithm based on the nonstructural data mining model

Under the background of the nonstructural data mining model, a Web text clustering mining algorithm based on the discovery feature sub-space model (DFSSM), W, TCDFSSM algorithm, was proposed, which can distinguish the most meaningful features from the concept space without any evaluation function. The WTCDFSSM algorithm was applied in the modern long-distance education net. The result shows that it can automatically congregate the text information of education field, which is collected from education sites on Internet, help people to browse the important information quickly by information navigation mechanism and acquire useful knowledge.