关键词: 平行坐标, 日志数据, 聚类, 自组织特征映射, 模糊c-均值

Abstract:

A double clustering model to make web log data sets clustering was proposed based on the self-organizing map (SOM) neural networks and the fuzzy c-means (FCM) method. The first tier uses unsupervised clustering method—SOM neural network, so the number of classes it generates significantly reduces compared with the original data set, it also reduces the FCM method's rely on class initial centers. Using the FCM clustering algorithm to cluster the center points of classes generated by the first layer, the time complexity of clustering is greatly reduced. Meanwhile, the parallel coordinates visualization technology to demonstrate the log dataset was used, it is suitable to analyze the log data.

Key words: parallel coordinates, log data, cluster, self-organizing map, fuzzy c-means