Abstract: Aimed at the situation that the plan attribute value is a three-parameter interval grey number and that attribute weight is uncertain, a three-parameter interval grey number multi-attribute decision making method based on information entropy is proposed. In this study, we combine the three-parameter interval grey number decision-making problem with information entropy, build the dista...

Event counting is significant when it allows us to discover and represent implicit knowledge. We realize that a particular event happens somewhere not just by mere chance, it is unlikely to be what we call as accidental event. E.g. the number of violent attacks and terrorist acts can give the measure of the safety for a given country and can help us to predict where and/or when similar events a...

We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and parallel surfaces in this space. It further uses sequences of images to obtain more reliable clustering. Finally, since our method relies on a non-Euclidean similarity measure we introduce algebraic techniques for estimat...

Context-aware computing applications often perform an assessment of similarity between the user’s current situation and the predefined or learned situations in order to trigger appropriate adaptation rules. Because future situations are often not exactly matching with past ones (e.g., time continuously changes), the assessment of similarity between situations is not a straightforward task. This...

In this paper, we propose a novel Fourier-theoretic approach for estimating the symmetry group G of a geometric object X. Our approach takes as input a geometric similarity matrix between low-order combinations of features of X and then searches within the tree of all feature permutations to detect the sparse subset that defines the symmetry group G of X. Using the Fouriertheoretic approach, we...

This article presents a distance and angle similarity measure. The integrated similarity measure takes the strengths of both the distance and direction of measured documents into account. This article analyzes the features of the similarity measure by comparing it with the traditional distance-based similarity measure and the cosine measure, providing the iso-similarity contour, investigating t...

We suggest to define objective probabilities by similarity-weighted empirical frequencies, where more similar cases get a higher weight in the computation of frequencies. This formula is justified intuitively and axiomatically, but raises the question, which similarity function should be used? We propose to estimate the similarity function from the data, and thus obtain objective probabilities....

Shape matching is an important issue in pattern recognition and it has many real world applications. We have proposed a two-stage framework for polygon retrieval 12, 11] which incorporates both qualitative and quantitative measures of polygons in the rst and second stage respectively. In this paper, we introduce an extension to our two-stage framework. We propose a new polygon matching techniqu...

Extracting the relevant information by exploiting the spatial data warehouse becomes increasingly hard. In fact, because of the enormous amount of data stored in the spatial data warehouse, the user, usually, don't know what part of the cube contain the relevant information and what the forthcoming query should be. As a solution, we propose to study the similarity between the behaviors of the u...

This paper argues that two apparently distinct modes of generalizing concepts abstracting rules and computing similarity to exemplars should both be seen as special cases of a more general Bayesian learning framework. Bayes explains the specific workings of these two modes which rules are abstracted, how similarity is measured as well as why generalization should appear ruleor similarity-based ...