Mining, discovering, and integrating process-oriented services has attracted growing attention in the recent year. Workflow precedence graph and workflow block structures are two important factors for comparing and mining processes based on distance similarity measure. Some existing work has done on comparing workflow designs based on their precedence graphs. However, there lacks of standard di...

Optimal feature subset selection is an important pre-processing step for classification in many real life problems where number of dimensions of feature space is large and some features are may be irrelevant or redundant. One example of such a situation is genes expression profile data to classify among normal and cancerous samples. Contribution of this paper is five folds. Similarity-dissimila...

This paper considers two major applications of shape matching algorithms: (a) query-by-example, i. e. retrieving the most similar shapes from a database and (b) finding clusters of shapes, each represented by a single prototype. Our approach goes beyond pairwise shape similarity analysis by considering the underlying structure of the shape manifold, which is estimated from the shape similarity ...

We propose a model for three judgments involving a measure of similarity and dissimilarity between faces: the similarity judgment (Sj), the dissimilarity judgment (Dj), and the kinship judgment (Kj), which has been demonstrated to be strongly related to the Sj (Lorusso et al., 2011; Maloney & Dal Martello, 2006). A previous model for Sj and Kj between faces (see i.e., Maloney & Dal Martello, 20...

Pairwise clustering methods partition the data space into clusters by the pairwise similarity between data points. The success of pairwise clustering largely depends on the pairwise similarity function defined over the data points, where kernel similarity is broadly used. In this paper, we present a novel pairwise clustering framework by bridging the gap between clustering and multi-class class...

Triangular designs analyzed by contemporary nonmetric scaling procedures can yield estimated scales that are nonlinearly related to the "true" scale values. In nonmetric unidimensional scaling, observers rate the "difference," "similarity," or "dissimilarity" of stimulus pairs, and a subtractive model is used to estimate scale values that will reproduce the rank order of the judgments. For exam...