Shape matching is an important ingredient in shape retrieval, recognition and classification, alignment and registration, and approximation and simplification. This paper treats various aspects that are needed to solve shape matching problems: choosing the precise problem, selecting the properties of the similarity measure that are needed for the problem, choosing the specific similarity measur...

This paper reviews and extends the field of similarity-based classification, presenting new analyses, algorithms, data sets, and a comprehensive set of experimental results for a rich collection of classification problems. Specifically, the generalizability of using similarities as features is analyzed, design goals and methods for weighting nearest-neighbors for similarity-based learning are p...

We deal with two independent but related problems, those of graph similarity and subgraph matching, which are both important practical problems useful in several fields of science, engineering and data analysis. For the problem of graph similarity, we develop and test a new framework for solving the problem using belief propagation and related ideas. For the subgraph matching problem, we develo...

A basic problem in classifying, or searching for similar objects in, a large set of geometric objects is computing similarity between two objects. This has led to extensive work on computing geometric similarity between two objects. This talk discusses some old and some new geometric-similarity algorithms, with an emphasis on transportation distance (also called earth mover’s distance) and Frec...

Recommendation systems provide customers with personalized recommendations by analyzing the purchase history. Item-based Collaborative Filtering (CF) algorithms recommend items which are similar to what the customers purchased before. Item-based algorithms are widely employed over user-based algorithms due to less computational complexity and better accuracy. We implement several types of item-...

Search operations in large sets of complex objects usually rely on similarity-based criteria, due to the lack of other general properties that could be used to compare the objects, such as the total order relationship, or even the equality relationship between pairs of objects, commonly used with data in numeric or short texts domains. Therefore, similarity between objects is the core criterion...

normal 0 false false false en-us x-none fa background:  regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. the method of segmentation is used to analyze anal to miscall structures in medical imaging. objective:  this study describes a new method for brain magnetic resonance image (mri) segmentation via a ...

Knowledge about algorithm similarity is an important feature of meta-learning, where information gathered from previous learning tasks can be used to guide the selection or combination of algorithms for a new dataset. Usually this task is done by comparing global performance measures across different datasets or, alternatively, comparing the performance of algorithms at the instance-level. Thes...

The classification process support algorithms of shooting hyperspectral data, realizing objects’ identification of the Earth’s surface by means of their hyperspectral features’ analysis, received from the processed space images with application of various similarity measures, are considered. Identification algorithms on the base of Euclidean distance similarity measure, angular similarity measu...

Multiple structure alignment (MStA) is a fundamental tool for correlating the structural similarity of proteins with their functional similarity. A number algorithms are extant, MUSTANG, POSA, M...