Clustering algorithm in Deep Web based on Chinese word segmentation
Liu Ronghui, Jianguo Zheng · Computer Engineering and Applications Journal · 2011
With the rapid development of Deep Web,it is especially important to extract quality data and process them from Web database by query interface on e-business sites.In this paper,searched pages are obtained to make use of query interface by dynamically submitting key words.Chinese item information is extracted from searched pages and segmented.The segmentation result is analyzed statistically to reduce dimensionality based on DF to get feature items.TF/IDF is used to calculate the weight vector matrix getting the feature item weight vector matrix.Weight vector matrix is presented to cluster the searched datum.The experiment results show the correctness and feasibility of this algorithm.