期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：5
出版社：IJCSI Press
摘要：The hierarchy is often used to infer knowledge from groups of items and relations in varying granularities. Hierarchical clustering algorithms take an input of pairwise data-item similarities and output a hierarchy of the data-items. This paper presents Bidirectional agglomerative hierarchical clustering to create a hierarchy bottom-up, by iteratively merging the closest pair of data-items into one cluster. The result is a rooted AVL tree. The n leafs correspond to input data-items (singleton clusters) needs to n/2 or n/2+1 steps to merge into one cluster, correspond to groupings of items in coarser granularities climbing towards the root. As observed from the time complexity and number of steps need to cluster all data points into one cluster perspective, the performance of the bidirectional agglomerative algorithm using AVL tree is better than the current agglomerative algorithms. The experiment analysis results indicate that the improved algorithm has a higher efficiency than previous methods.
关键词：Hierarchical; Clustering; Bidirectional algorithm; Agglomerative; AVL tree
