Significant locations in auxiliary data as seeds for typical use cases of point clustering

Kröger, Johannes

Random greedy clustering and grid-based clustering are highly susceptible by their initial parameters. When used for point data clustering in maps they often change the apparent distribution of the underlying data. We propose a process that uses precomputed weighted seed points for the initialization of clusters, for example from local maxima in population density data. Exemplary results from the clustering of a dataset of petrol stations are presented.

Zitieren

Zitierform:

Kröger, Johannes: Significant locations in auxiliary data as seeds for typical use cases of point clustering. 2018. Copernicus Publications.

Zugriffsstatistik

Gesamt:
Volltextzugriffe:
Metadatenansicht:
12 Monate:
Volltextzugriffe:
Metadatenansicht:

Grafik öffnen

Rechte

Rechteinhaber: Johannes Kröger

Nutzung und Vervielfältigung:

Export