用于Web导航模式聚类的增量SOM

26th International Conference on Information Technology Interfaces, 2004. Pub Date : 2004-06-07 DOI:10.1109/ITI.2004.241604

K. Benabdeslem, Younès Bennani

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引用次数: 6

摘要

本文提出了一种新的聚类方法，它使无监督神经模型(自组织映射:SOM)的构造渐进式地进行。换句话说，该方法同时计算基于先验可用数据的初始模型和在给定时间内动态到达的数据。该方法在Web导航数据上进行了验证，并与应用于相同数据的经典神经聚类进行了比较

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An incremental SOM for Web navigation patterns clustering

In this paper, we present a new clustering method which makes incremental the construction of an unsupervised neural model (self organizing map: SOM). In other words, the method is computed with both, the initial model based on the a priori available data and the data which arrive dynamically in the time. This approach is validated over Web navigation data and it is compared to classical neural clustering applied to the same data

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26th International Conference on Information Technology Interfaces, 2004.

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