Due to computational and storage efficiencies of compact binary codes, hashing has been widely used for large-scale similarity search. Unfortunately, many existing hashing methods based on observed keyword features are not effective for short texts due to the sparseness and shortness. Recently, some researchers try to utilize latent topics of certain granularity to preserve semantic similarity ...

Learning hash functions/codes for similarity search over multi-view data is attracting increasing attention, where similar hash codes are assigned to the data objects characterizing consistently neighborhood relationship across views. Traditional methods in this category inherently suffer three limitations: 1) they commonly adopt a two-stage scheme where similarity matrix is first constructed, ...

We extend the results obtained for different cases of the product superposition of periodic functions, and the determination of the scattered fields, for the case of circular symmetry. The characteristics of focalization for such cases are studied. We name Cantor-Fresnel zone plate the structures obtained with this method. Also, in this study can be included the focalization by periodic, Cantor...

palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. texture is one of the most important features extracted from low resolution images. in this paper, a new local descriptor, local composition derivative pattern (lcdp) is proposed to extract smartly stronger...

The majority of the intelligent knowledge-based applications include elements for the purpose of measuring semantic similarity stuck between terms. A lot of the available semantic similarity measures that make use of ontology structure as their chief source cannot determine semantic similarity among terms and concepts by means of multiple ontologies. Hence, this research looks for a new approac...

The design of a CBR system involves the use of similarity metrics. For many applications, various functions can be adopted to compare case features and to aggregate them into a global similarity measure. Given the availability of multiple similarity metrics, the designer is hence left with two options in order to come up with a working system: Either select one similarity metric or try to combi...

D.Chandramohan, Shailesh Khapre, S.Ashokkumar Abstract— Newest mounting and escalated recognition of services and its equivalent building of significant Web service mature to be a considerable rally. Web service expertise for permitting right to entry for promoting services regardless of locality and execution policies exist already. On the other hand, a huge discrepancy on structural, semantic...

In this paper, a new graph data structure for 2-D shape representation is proposed. The new structure is called a concavity graph, and is an evolution from the already known “concavity tree”. Even though a concavity graph bears a fundamental resemblance to a concavity tree, the former is able to describe the shape of multiple objects in an image and their spatial configuration, and is hence inh...

Semantic similarity measures have been used successfully and extensively in the biomedical research with various applications. As the biomedical ontologies, which form the main ground for most of the similarity measures, are growing and progressing towards more completeness and higher accuracy, the results and outcomes of these semantic similarity measures become more acceptable and more reliab...

This paper provides a novel solution to the volumetric similarity registration problem usually encountered in statistical study of shapes and shape-based image segmentation. Here, shapes are implicitly represented by characteristic functions (CFs). By mapping shapes to a spherical coordinate system, shapes to be registered are projected to unit spheres and thus, rotation and scale parameters ca...