Since its inception, the full Lagrangian meshless smoothed particle hydrodynamics (SPH)
has experienced a tremendous enhancement in methodology and impacted a range of multi …

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 …

At SIGMOD 2015, an article was presented with the title “DBSCAN Revisited: Mis-Claim, Un-
Fixability, and Approximation” that won the conference's best paper award. In this technical …

This well-accepted introduction to computational geometry is a textbook for high-level
undergraduate and low-level graduate courses. The focus is on algorithms and hence the …

In order to handle spatial data efficiently, as required in computer aided design and geo-
data applications, a database system needs an index mechanism that will help it retrieve …

The Handbook of Discrete and Computational Geometry is intended as a reference book
fully accessible to nonspecialists as well as specialists, covering all major aspects of both …

Machine learning, especially deep learning, is used increasingly to enable better solutions
for data management tasks previously solved by other means, including database indexing …

The present book provides an introduction to using space-filling curves (SFC) as tools in
scientific computing. Special focus is laid on the representation of SFC and on resulting …

Data sets in large applications are often too massive to fit completely inside the computers
internal memory. The resulting input/output communication (or I/O) between fast internal …

Nearest neighbor search is a fundamental problem in various research fields like machine
learning, data mining and pattern recognition. Recently, hashing-based approaches, for …