The past decade has been characterized by the growing volumes of data due to the
widespread use of the Internet of Things (IoT) applications, which introduced many …

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 …

As the number of digital images is growing fast and Content-based Image Retrieval (CBIR)
is gaining in popularity, CBIR systems should leap towards Web-scale datasets. In this …

The need for a retrieval based not on the attribute values but on the very data content has
recently led to rise of the metric-based similarity search. The computational complexity of …

In recent years, the number of sensor and actuator nodes in the Internet of Things (IoT)
networks has increased, generating a large amount of data. Most research techniques are …

In this paper we present a scalable and distributed access structure for similarity search in
metric spaces. The approach is based on the Content–addressable Network (CAN) …

Similarity queries, including range queries and k nearest neighbor (k NN) queries, in metric
spaces have applications in many areas such as multimedia retrieval, computational biology …

US8983989B2 - Contextual queries - Google Patents US8983989B2 - Contextual queries -
Google Patents Contextual queries Download PDF Info Publication number US8983989B2 …

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

Finding similar objects based on a query and a distance, remains a fundamental problem for
many applications. The general problem of many similarity measures is to focus the search …