22 citations · 55 across the 10 of their papers we have counts for
5 papers · 1 filter
S-RASTER: Contraction Clustering for Evolving Data Streams
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Contraction Clustering (RASTER) is a single-pass algorithm for density-based clustering of 2D data. It can process arbitrary amounts of data in linear time and in constant memory,…
Active-Code Replacement in the OODIDA Data Analytics Platform
Gregor Ulm, Emil Gustavsson, Mats Jirstrand
OODIDA (On-board/Off-board Distributed Data Analytics) is a platform for distributing and executing concurrent data analytics tasks. It targets fleets of reference vehicles in the…
Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Clustering is an essential data mining tool for analyzing and grouping similar objects. In big data applications, however, many clustering algorithms are infeasible due to their hi…
Facilitating Rapid Prototyping in the OODIDA Data Analytics Platform via Active-Code Replacement
Gregor Ulm, Simon Smith, Adrian Nilsson +2
OODIDA (On-board/Off-board Distributed Data Analytics) is a platform for distributed real-time analytics, targeting fleets of reference vehicles in the automotive industry. Its use…
OODIDA: On-board/Off-board Distributed Real-Time Data Analytics for Connected Vehicles
Gregor Ulm, Simon Smith, Adrian Nilsson +2
A fleet of connected vehicles easily produces many gigabytes of data per hour, making centralized (off-board) data processing impractical. In addition, there is the issue of distri…