Most link prediction algorithms only consider local or global characteristics of the graph, so it is difficult to reach equilibrium in the accuracy and the computational complexity. And the research on link prediction in weighted networks is relatively less. A new algorithm STNMP (Similarity based on Transmission Nodes of Multiple Paths) for link prediction in weighted social networks is propos...

Local similarity is an important tool in comparative analysis of biological sequences, and is therefore well studied. In particular, the Smith-Waterman technique and its normalized version are two established metrics for measuring local similarity in strings. In RNA sequences however, where one must consider not only sequential but also structural features of the inspected molecules, the concep...

ultrasound images suffer of multiplicative noise named speckle. different de-speckling algorithms run either in spatial domain or in transformed domain. in this paper, an adaptive filter in spatial domain according to assume the nakagami distribution as the statistic of log-compressed ultrasound images is used. for de-speckling in transformed domain, the non-sub sampled shearlet transform is us...

We present similarity-based methods to cluster digital photos by time and image content. This approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We describe versions of the algorithm using temporal similarity with and without content-based similarity, and compare the algorithms with existing techniques, measured agains...

1 Introduction We introduce a new approach for similarity search in 3-D protein databases. By using histograms, we define adaptable similarity models that address the 3-D shape as well as chemical properties of proteins. Quadratic forms are employed as similarity distance functions for which efficient query processing algorithms are available [Sei 97]. Experimental examples illustrate the appli...

Clustering is an important data mining technique. There are many algorithms that cluster either numeric or categorical data. However few algorithms cluster mixed type datasets with both numerical and categorical attributes. In this paper, we propose a similarity measure between two clusters that enables hierarchical clustering of data with numerical and categorical attributes. This similarity m...

This paper proposes an oriented Hausdorff similarity measure for object matching. The oriented Hausdorff distance (HD) measure is introduced by replacing the distance concept of conventional HD algorithms by a similarity measure. The orientation at each ~ i x e l is used for removing incorrect correspondences. Various experiments show that the perFigure 1: Block diagram for the Hausdorff distan...

This paper focuses on gathering similarity ratings for use in the construction, optimization and evaluation of melodic similarity algorithms. The approach involves conducting listening experiments to gather these ratings for a piece in Theme and Variation form.

Due to the frequency of spelling and typographical errors in practical applications, record linkage algorithms have to use string similarity functions. In many legal contexts, identifiers such as names have to be encrypted before a record linkage can be attempted. Therefore, algorithms for computing string similarity functions with encrypted identifiers are essential for approximating string ma...

Text similarity detection aims at measuring the degree of similarity between a pair of texts. Corpora available for text similarity detection are designed to evaluate the algorithms to assess the paraphrase level among documents. In this paper we present a textual German corpus for similarity detection. The purpose of this corpus is to automatically assess the similarity between a pair of texts...