【作者】 刘建伟； 于守健； 乐嘉锦；

【机构】 东华大学信息科学与技术学院；

【摘要】 <正>1简介在大多数Web页面中,大量的有用的知识隐藏在Web文本中。对于这些海量的文本数据,利用挖掘工具有效地把文本数据组织成为结构化的知识,将会显著地提高Web页面访问效率。Web已经变更多还原

【Abstract】 Given the popularity of Web news services,we focus our attention on mining hierarchical topic from Web news stream data.To address this problem,we present a Divisive-Agglomerative clustering method to find hierarchical topic from Web news stream.The novelty of the proposed algorithm is the ability to identify meaningful news topics while reducing the amount of computations by maintaining dynamic cluster structure incrementally.Our streaming news clustering algorithm also works by leveraging off the nearest neighbors of the incoming streaming news datasets and has ability of identifying the different shapes and different densities of clusters.Experimental results demonstrate that the proposed clustering algorithm produces high-quality topic discovery.更多还原