Density-Based Clustering Validation

By Davoud Moulavi, Pablo A. Jaskowiak, Ricardo José Gabrielli Barreto Campello, Arthur Zimek, Jörg Sander. SDM, 2014

330 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a40fb167d9d658242017ef6bc59a2f3933c2fded

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Arthur Zimek
2. Jörg Sander
3. Ricardo José Gabrielli Barreto Campello
4. Peer Kröger
5. Charu C. Aggarwal
6. Hans-Peter Kriegel
7. Erich Schubert
8. Hongzhi Wang

In Statistical and Nonlinear Physics

1. Jörg Sander
2. Ricardo José Gabrielli Barreto Campello
3. Peer Kröger
4. Arthur Zimek

In Signal Processing

1. Arthur Zimek
2. Jörg Sander
3. Ricardo José Gabrielli Barreto Campello
4. Peer Kröger
5. René Vidal
6. Hans-Peter Kriegel
7. D. Angelov
8. Joseph Homer Saleh

Citations in the corpus

• Density‐based clustering (2019, methodology): “…— to adjust for the special characteristics of density-based clusters, which are not necessarily compact and separated in the original data space according to a Euclidean perspective, however these methods fall short in different respects (Moulavi, Jaskowiak, Campello, Zimek, & Sander, 2014).”
• A Large-Language-Model Framework for Automated Humanitarian Situation Reporting (2025, unknown): “First, we adopt the Density-Based Clustering Validation (DBCV) index 32 , specifically designed to assess the quality of density-based cluster structures 31 .”