k nearest neighbours (kNN) queries are fundamental in many applications, ranging from
data mining, recommendation system and Internet of Things, to Industry 4.0 framework …

Similarity searches retrieve elements in a dataset with similar characteristics to the input
query element. Recent works show that graph-based methods have outperformed others in …

Given a user dataset U and an object dataset I, a kNN join query in high-dimensional space
returns the k nearest neighbors of each object in dataset U from the object dataset I. The …

The k nearest neighbor (kNN) join operation is a fundamental task that combines two high-
dimensional databases, enabling data points in the User dataset U to identify their k nearest …

As an alternative to resource-intensive deep learning approaches to the continual learning
problem, we propose a simple, fast algorithm inspired by adaptive resonance theory (ART) …

Given a user dataset U and an object dataset I, a kNN join query in high-dimensional space
returns the k nearest neighbors of each object in dataset U from the object dataset I. The …