The area of similarity searching is a very hot topic for both research and c-mercial
applications. Current data processing applications use data with c-siderably less structure …

The task of similarity search is widely used in various areas of computing, including
multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of …

With the continued digitization of societal processes, we are seeing an explosion in
available data. This is referred to as big data. In a research setting, three aspects of the data …

Similarity search in graph databases is one of the most fundamental operations in graph
analytics. Among various distance functions, graph and subgraph edit distances (GED and …

The metric space model abstracts many proximity search problems, from nearest-neighbor
classifiers to textual and multimedia information retrieval. In this context, an index is a data …

Metric space is a universal and versatile model of similarity that can be applied in various
areas of information retrieval. However, a general, efficient, and scalable solution for metric …

Graph analysis is a powerful method in data analysis. Although several frameworks have
been proposed for processing large graph instances in distributed environments, their …

Similarity join algorithms find pairs of objects that lie within a certain distance ε of each other.
Algorithms that are adapted from spatial join techniques are designed primarily for data in a …

The similarity search has become a fundamental computational task in many applications.
One of the mathematical models of the similarity–the metric space–has drawn attention of …

The general notion of a metric space encompasses a diverse range of data types and
accompanying similarity measures. Hence, metric search plays an important role in a wide …