Similarity indices for high-dimensional data are very desirable for building content-based search systems for featurerich data such as audio, images, videos, and other sensor data. Recently, locality sensitive hashing (LSH) and its variations have been proposed as indexing techniques for approximate similarity search. A significant drawback of these approaches is the requirement for a large num...

This study develops an interactive clustering model and methodology for high dimensional data. The similarity index is calculated with proposed formulation for both continuous-scaled and nominal-scaled attributes. The associated similarity score values are constructed into a graph as clique partitioning problem, which can be reformulated into a form of unconstrained quadratic program model and ...

Three possible determinants of typicality were examined in categories of common household objects: family resemblance and an exemplar’s similarity to a geometrical centroid of the category, either unweighted or weighted for name frequencies. Similarity to the geometrical centroids in 2to 6-dimensional spaces outperformed family resemblance in predicting typicality. Finally, optimizing the predi...

The degree of similarity of two protein three-dimensional structures is usually measured with the root-mean-square distance between equivalent atom pairs. Such a similarity measure depends on the dimension of the proteins, that is, on the number of equivalent atom pairs. The present communication presents a simple procedure to make the root-mean-square distances between pairs of three-dimension...

Many emerging data mining applications require a similarity join between points in a highdimensional domain. We present a new algorithm that utilizes a new index structure, called the -kdB tree, for fast spatial similarity joins on high-dimensional points. This index structure reduces the number of neighboring leaf nodes that are considered for the join test, as well as the traversal cost of nd...

Multidimensional similarity join finds pairs of multidimensional points that are within some small distance of each other. The -k-d-B tree has been proposed as a data structure that scales better as the number of dimensions increases compared to previous data structures. We present a cost model of the -k-d-B tree and use it to optimize the leaf

The methods described by Bluman & Cole (1974) are used to derive the infinitesimals of the general invariance group of the unsteady, two-dimensional, stream-function equation for the case where the kinematic viscosity v is equal to a constant and the case where v = 0. The infinitesimals in each case involve ten independent parameters, seven of which appear explicitly and three of which are cont...

RATIONALE AND OBJECTIVES The creation of two-dimensional (2D) ultrasound mosaics is becoming a common clinical practice with a high clinical value. The next step coming along with the increasing availability of 2D array transducers is the creation of three-dimensional mosaics. The correct alignment of multiple ultrasound images is, however, a complex task. In the literature of ultrasound regist...

Outline shape carries a substantial part of the information present in an object view, and is more economical than classical representations such as geon-structural-descriptions or multiple-views. We demonstrate the utility of silhouette representations for a variety of visual tasks, ranging from basic-level categorization to nding the best view of an object. All these tasks necessitate the com...

ÐCurrent data repositories include a variety of data types, including audio, images, and time series. State-of-the-art techniques for indexing such data and doing query processing rely on a transformation of data elements into points in a multidimensional feature space. Indexing and query processing then take place in the feature space. In this paper, we study algorithms for finding relationshi...