A numerical solution of the steady boundary layer equations under similarity assumptions is obtained for the three-dimensional flow of a micropolar fluid over a continuous stretching surface. The case when microrotation vector is zero on the solid surface is considered. Using properly similarity variables, the three-dimensional Navier – Stokes equations are reduced to a set of four coupled non-...

Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM), with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based b...

Motivated by evidence in psycholinguistics and cognition, we propose a hierarchical distributed semantic model (DSM) that consists of low-dimensional manifolds built on semantic neighborhoods. Each semantic neighborhood is sparsely encoded and mapped into a low-dimensional space. Global operations are decomposed into local operations in multiple sub-spaces; results from these local operations a...

Many NLP applications rely on the existence of similarity measures over text data. Although word vector space models provide good similarity measures between words, phrasal and sentential similarities derived from composition of individual words remain as a difficult problem. In this paper, we propose a new method of of non-linear similarity learning for semantic compositionality. In this metho...

In this paper we present a clustering and indexing paradigm (called Clindex) for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where one wishes to find many of the data points near a target point, but where one can tolerate missing a few near points. For such searches, our scheme can find near points with high recall in very few IOs and perform sign...

Given a database D of three-dimensional (3D) molecular structures and a target molecule Q, the similarity search problem is to find the molecules O in D that match Q after allowing for an arbitrary number of whole-structure rotations and translations as well as a certain number of edit operations. The edit operations include relabeling an atom, deleting an atom, and inserting an atom. This sear...

Searching and mining nuclear magnetic resonance (NMR)spectra of naturally occurring products is an important task to investigate new potentially useful chemical compounds. We develop a set-based similarity function, which, however, does not sufficiently capture more abstract aspects of similarity. NMR-spectra are like documents, but consists of continuous multi-dimensional points instead of wor...

In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate similarity measure for the particular feature space, as there is usually only little knowledge about the structure of that space. As a possible solution to this problem this paper presents a method to obtain a similarit...

Similarity has been proposed as a fundamental principle underlying mental object representations and capable of supporting cognitive-level tasks such as categorization. However, much of the research has considered connections between similarity and categorization for tasks performed using a single perceptual modality. Considering similarity and categorization within a multimodal context opens u...