DBSCAN revisited, revisited: why and how You should (still) use DBSCAN

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 correspondence, we want to point out some inaccuracies in the way DBSCAN was represented, and why the criticism should...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Schubert, Erich (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: March 2017
In: ACM transactions on database systems
Year: 2017, Jahrgang: 42, Heft: 3, Pages: 19
ISSN:0362-5915
DOI:10.1145/3068335
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1145/3068335
Verlag, Volltext: http://doi.acm.org/10.1145/3068335
Volltext
Verfasserangaben:Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, Xiaowei Xu
Beschreibung
Zusammenfassung: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 correspondence, we want to point out some inaccuracies in the way DBSCAN was represented, and why the criticism should have been directed at the assumption about the performance of spatial index structures such as R-trees and not at an algorithm that can use such indexes. We will also discuss the relationship of DBSCAN performance and the indexability of the dataset, and discuss some heuristics for choosing appropriate DBSCAN parameters. Some indicators of bad parameters will be proposed to help guide future users of this algorithm in choosing parameters such as to obtain both meaningful results and good performance. In new experiments, we show that the new SIGMOD 2015 methods do not appear to offer practical benefits if the DBSCAN parameters are well chosen and thus they are primarily of theoretical interest. In conclusion, the original DBSCAN algorithm with effective indexes and reasonably chosen parameter values performs competitively compared to the method proposed by Gan and Tao.
Beschreibung:Gesehen am 12.04.2018
Beschreibung:Online Resource
ISSN:0362-5915
DOI:10.1145/3068335