In this work we propose a hierarchical clustering methodology for hyperspectral data based on the Hotelling’s T 2 statistic. For each hypespectral sample data, the statistical sample mean is calculated using a window-based neighborhood. Then, the pairwise similarities between any two hyperspectral samples are computed in base to the Hotelling’s T 2 statistic. This statistic assumes a Gaussian d...

The problem of hierarchical clustering items from pairwise similarities is found across various scientific disciplines, from biology to networking. Often, applications of clustering techniques are limited by the cost of obtaining similarities between pairs of items. While prior work has been developed to reconstruct clustering using a significantly reduced set of pairwise similarities via adapt...

Our paper is concerned with investigating the impact of translationese on the novels of a bilingual writer and asking whether one could determine the authorship of a translated document. The main part of our paper will be centered on selecting a good set of lexical features that can be considered characteristic for an author. We used in our research the novels of Vladimir Nabokov, a bilingual a...

Clustering is the assignment of data objects (records) into groups (called clusters) so that data objects from the same cluster are more similar to each other than objects from different clusters. Clustering techniques have been discussed extensively in similarity search, Segmentation, Statistics ,Machine Learning ,Trend Analysis, Pattern Recognition and classification. Clustering methods can b...

Hierarchical approaches, which are dominated by the generic agglomerative clustering algorithm, are suitable for cases in which the count of distinct clusters in the data is not known a priori; this is not a rare case in real data. On the other hand, important problems are related to their application, such as susceptibility to errors in the initial steps that propagate all the way to the final...

This paper proposes a hybrid data mining approach to quantitatively analyze product complexity of prefabricated construction components from product nonconforming quality performance data. The proposed model is constructed in three steps, which (1) measure product complexity by introducing a Bayesian-based nonconforming quality performance indicator; (2) score each type of product complexity by...