Bioinformatics emerged as a challenging new area of research and brought forth numerous computational problems. Here computers are used to gather, store, analyze and merge biological data. In this paper, the problem of clustering interval-scaled data and sequence data is analyzed in a new approach using Hierarchical Sequence Clustering. In Sequence clustering, it is necessary to find the simila...

This paper addresses the problem of cluster defining criteria by proposing a model-based characterization of interpattern relationships. Taking a dissimilarity matrix between patterns as the basic measure for extracting group structure, dissimilarity increments between neighboring patterns within a cluster are analyzed. Empirical evidence suggests modeling the statistical distribution of these ...

Partial orders and directed acyclic graphs are commonly recurring data structures that arise naturally in numerous domains applications used to represent ordered relations between entities the domains. Examples task dependencies a project plan, transaction order distributed ledgers execution sequences of tasks computer programs, just mention few. We study problem preserving hierarchical cluster...

A new unsupervised classification algorithm is introduced for fully polarimetric SAR data. The agglomerative hierarchical algorithm and Wishart test statistics are used for the cluster segmentation, which includes the process of estimation the number of clusters. The Cloude-Pottier decomposition & HSI color transform are used for the target identification, which also automatically render the co...

Disease mapping aims to estimate the spatial pattern in disease risk across an area, identifying units which have elevated disease risk. Existing methods use Bayesian hierarchical models with spatially smooth conditional autoregressive priors to estimate risk, but these methods are unable to identify the geographical extent of spatially contiguous high-risk clusters of areal units. Our proposed...

This paper introduces a variant of agglomerative hierarchical clustering techniques. The new technique is used for categorizing character shapes (allographs) in large data sets of handwriting into a hierarchical structure. Such a technique may be used as the basis for a systematic naming scheme of character shapes. Problems with existing methods are described and the proposed method is explaine...

Author co-citation analysis (ACA) has been widely used in bibliometrics as an analytical method in analyzing the intellectual structure of science studies. It can be used to identify authors from the same or similar research fields. However, such analysis method relies heavily on statistical tools to perform the analysis and requires human interpretation. Web Citation Database is a data warehou...