Building a web‐snippet clustering system based on a mixed clustering method

Purpose – Web‐snippet clustering has recently attracted a lot of attention as a means to provide users with a succinct overview of relevant results compared with traditional search results. This paper seeks to research the building of a web‐snippet clustering system, based on a mixed clustering method. Design/methodology/approach – This paper proposes a mixed clustering method to organise all returned snippets into a hierarchical tree. The method accomplishes two main tasks: one is to construct the cluster labels and the other is to build a hierarchical tree. Findings – Five measures were used to measure the quality of clustering results. Based on the results of the experiments, it was concluded that the performance of the system is better than current commercial and academic systems. Originality/value – A high performance system is presented, based on the clustering method. A divisive hierarchical clustering algorithm is also developed to organise all returned snippets into a hierarchical tree.