Nearest neighbor search is a fundamental and essential operation in applications from
many domains, such as databases, machine learning, multimedia, and computer vision …

Index structures are one of the most important tools that DBAs leverage to improve the
performance of analytics and transactional workloads. However, building several indexes …

We propose a novel approach to solving the approximate k-nearest neighbor search
problem in metric spaces. The search structure is based on a navigable small world graph …

Nearest neighbor (NN) search in high dimensional space is an important problem in many
applications. Ideally, a practical solution (i) should be implementable in a relational …

Nearest neighbor searches in high-dimensional space have many important applications in
domains such as data mining, and multimedia databases. The problem is challenging due to …

Content-based copy retrieval (CBCR) aims at retrieving in a database all the modified
versions or the previous versions of a given candidate object. In this paper, we present a …

Data series are a special type of multidimensional data present in numerous domains,
where similarity search is a key operation that has been extensively studied in the data …

Nearest neighbor searching of large databases in high-dimensional spaces is inherently
difficult due to the curse of dimensionality. A flavor of approximation is, therefore, necessary …

Searching for high-dimensional vector data with high accuracy is an inevitable search
technology for various types of data. Graph-based indexes are known to reduce the query …

Efficient high-dimensional similarity search structures are essential for building scalable
content-based search systems on feature-rich multimedia data. In the last decade, Locality …