Clustering has been widely used to partition data into groups so that the degree of association is high among members of the same group and low among members of diierent groups. Though many eeective and eecient clustering algorithms have been developed and deployed, most of them still suuer from the lack of automatic or online decision for optimal number of clusters. In this paper, we deene clu...

In the election of a hierarchical clustering method, theoretic properties may give some insight to determine which method is the most suitable to treat a clustering problem. Herein, we study some basic properties of two hierarchical clustering methods: α-unchaining single linkage or SL(α) and a modified version of this one, SL∗(α). We compare the results with the properties satisfied by the cla...

This paper examines the problem of clustering a sequence of objects that cannot be described with a predeened list of attributes (or variables). In many applications, such a crisp representation cannot be determined. An extension of the traditionnal propositionnal formalism is thus proposed, which allows objects to be represented as a set of components. The algorithm used for clustering is brie...

We propose a method for segmentation of ex-pository texts based on hierarchical agglomera-tive clustering. The method uses paragraphs as the basic segments for identifying hierarchical discourse structure in the text, applying lexical similarity between them as the proximity test. Linear segmentation can be induced from the identified structure through application of two simple rules. However t...

The Minimum Quartet Tree Cost problem is to construct an optimal weight tree from the 3 (

This paper presents a clustering algorithm for dot patterns in n-dimensional space. The n-dimensional space often represents a multivariate (nf -dimensional) function in a ns-dimensional space (ns + nf = n). The proposed algorithm decomposes the clustering problem into the two lower dimensional problems. Clustering in nf -dimensional space is performed to detect the sets of dots in n-dimensiona...

For the past decade, the need of multimedia mining has increased tremendously, especially in image data due to inexpensive digital technologies and fast mounting of image data. In this paper, we, first, show an algorithm, SpIBag (Spatial Item Bag Mining), which discovers frequent spatial patterns in images. Due to the properties of image data, SpIBag considers a bag of items together with a spa...