Hierarchical Clustering is a procedure of cluster analysis which aims to construct a hierarchy of clusters. There are two kinds of hierarchical clustering i.e. Agglomerative, which is a bottom – up approach, where all the observations start in its own cluster, and pairs of clusters are merged moving up the hierarchy, and the other one is divisive, which is a top down approach, where each observ...

The recently proposed speaker diarization technique based on binary keys provides a very fast alternative to state-of-the-art systems with little increase of Diarization Error Rate (DER). Although the approach shows great potential, it also presents issues, mainly in the stopping criterion. Therefore, exploring alternative clustering/stopping criterion approaches is needed. Recently some works ...

Hierarchical clustering algorithms can be agglomerative or divisive, depending on how partitions are formed. Such algorithms have advantages mainly related to the desired level of granularity the partition should have. The work described in this paper approaches two hierarchical algorithms, one agglomerative (and three of its variants) and the other divisive, focusing on their performance in un...

We present two results which arise from a model-based approach to hierarchical agglomerative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms – Ward’s method, single-link, complete-link, and a variant of group-average – are each equivalent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical b...

This paper presents fingerprint indexing based on graph information of minutiae, fingerprint classification and verification based on hierarchical agglomerative clustering technique. The proposed fingerprint indexing is invariant under translation and rotation. Its performance is evaluated in terms of several real-life datasets. The fingerprint database is clustered into five classes based on t...

BACKGROUND Clustering of multiple health-compromising behaviours is associated with an increased risk of various chronic diseases. There are few studies on patterns of clustering of multiple health-compromising behaviours in adolescents. Therefore, the aim of this study is to assess how six health-compromising behaviours, namely, low fruit consumption, high sweet consumption, less frequent toot...

One fundamental problem that confronts information retrieval is to efficiently support query with higher accuracy and less logic hops. This paper presents HSPIR (Hierarchical Semantic P2P-based Information Retrieval) that distributes document indices through the P2P network hierarchically based on documents semantics generated by Latent Semantic Indexing (LSI) [1]. HSPIR uses CAN [2] and Range ...

The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm. In this work we evaluate empirically this new approach to hierarchical clustering. We compare hierarchical clustering based on the Baire metric with (i) agglomerative hierarchical clustering, in terms of algo...