DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It is designed for either numerical or categorical data. Like the Ward agglomerative hierarchical clustering algorithm and the k-means partitioning algorithm, it is based on the minimization of the inertia criterion. Howev...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...

Hierarchical clustering is an important technique for hierarchical data exploration applications. However, most existing hierarchial methods are based on traditional one-side clustering, which is not effective for handling high dimensional data. In this paper, we develop a partitional hierarchical co-clustering framework and propose a Hierarchical Information-Theoretical Co-Clustering (HITCC) a...

Hierarchical clustering based on pairwise similarities is a common tool used in a broad range of scientific applications. However, in many problems it may be expensive to obtain or compute similarities between the items to be clustered. This paper investigates the hierarchical clustering of N items based on a small subset of pairwise similarities, significantly less than the complete set of N(N...

In the MediaEval 2016 Retrieving Diverse Social Images Task, we proposed a general framework based on agglomerative hierarchical clustering (AHC). We tested the provided credibility descriptors as a vector input for our AHC. The results on devset showed that this vector based on the credibility descriptors is the best feature, but unfortunately that is not confirmed on testset. To merge several...

The paper considers techniques for grouping objects that are described with many quantitative and qualitative attributes and may exist in several copies. Such multi-attribute objects may be represented as multisets or sets with repeating elements. Multiset characteristics and operations under an arbitrary number of multisets are determined. The various options for the objects’ aggregation (addi...

This paper presents the TITech summarization system participating in TAC2009. Specifically, we discuss our results for the Update track. We propose a new method for creating summaries by ordering sentences. After a draft summary is obtained, we conduct agglomerative hierarchical clustering on the sentences of the draft summary based on sentence associativity. Then we use a probabilistic method ...

Link Clustering (LC) is a relatively new method for detecting overlapping communities in networks. The basic principle of LC is to derive a transform matrix whose elements are composed of the link similarity of neighbor links based on the Jaccard distance calculation; then it applies hierarchical clustering to the transform matrix and uses a measure of partition density on the resulting dendrog...