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Clustering Navigation Patterns using Closed Repetitive Gapped Subsequence

机译:使用闭合重复的覆盖子序列的聚类导航模式

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Categorizing visitors based on their navigation patterns on a website is a key problem in electronic logistics. However, user navigation data and feature vector extracted from it are sparse, and traditional clustering method doesn't solve this problem satisfactorily. As a step forward, a closed repetitive gapped subsequence mining based navigation pattern clustering method is proposed. Feature vector of navigation patterns is constructed with repetitive support of subsequence. A bidirectional projected Euclidean distance based fuzzy dissimilarity is proposed and used as distance measure of feature vectors. Experiment result show that this clustering method is effective and efficient.
机译:根据其导航模式对访问者进行分类是电子物流中的关键问题。但是,从它提取的用户导航数据和特征向量是稀疏的,传统的聚类方法并不能令人满意地解决这个问题。作为前进的一步,提出了一种基于闭合的重复覆盖子级挖掘的导航模式聚类方法。导航模式的特征向量是通过重复支持的重复支持。提出了一种双向预定的欧几里德距离的模糊异化,并用作特征向量的距离测量。实验结果表明,这种聚类方法是有效且有效的。

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