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 ...

Semi-analytical models of galaxy formation based on hierarchical clustering now make a wide range of predictions for observable properties of galaxies at low and high redshift. This article concentrates on 2 aspects: (1) Self-consistent modelling of dust absorption predicts a mean UV extinction AUV ∼ 1 mag, depending only weakly on redshift, and similar to observational estimates. (2) The model...

In this paper, we consider that agents judge the feasible alternatives through linguistic terms –when they are confident in their opinions– or linguistic expressions formed by several consecutive linguistic terms –when they hesitate. In this context, we propose an agglomerative hierarchical clustering process where the clusters of agents are generated by using a distance-based consensus measure.

Article history: Received 25 September 2007 Received in revised form 21 May 2008 Available online 22 July 2008 Communicated by L. Heutte

We present a short introduction to an hierarchical clustering method of high-dimensional data via localized

This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different clustering algorithms can yield different analyses of the same data set, and that there is no obvious way...

This paper presents a case study to show the competence of our evolutionary and visual framework for cluster analysis of DNA microarray data. The proposed framework joins a genetic algorithm for hierarchical clustering with a set of visual components of cluster tasks given by a tool. The cluster visualization tool allows us to display different views of clustering results as a means of cluster ...