Hybrid clustering with application to Web mining

Clustering algorithms fall into two categories: hierarchical clustering and partitional clustering. For hierarchical algorithms, they are static in the sense that they never undo what was done previously, which means that, objects which are committed to a cluster in the early stages, cannot move to another cluster. Partitional clustering does not suffer from this problem, but requires a pre-specified number for the output clusters. This paper presents a hybrid clustering method that combines the advantages of hierarchical clustering and partitional clustering techniques. The proposed hybrid algorithm does not require a number for the output clusters prior to the clustering and the clusters can be rearranged according to a quality measurement. In the present paper, we apply this method to Web page clustering and provide necessary experimental results.