Robust projected clustering

Gabriela Moise , Jörg Sander , Martin Ester
Knowledge and Information Systems 14 ( 3) 273 -298

64
2008
Subspace and projected clustering: experimental evaluation and analysis

Gabriela Moise , Arthur Zimek , Peer Kröger , Hans-Peter Kriegel
Knowledge and Information Systems 21 ( 3) 299 -326

60
2009
A unified framework of density-based clustering for semi-supervised classification

Jadson Castro Gertrudes , Arthur Zimek , Jörg Sander , Ricardo J. G. B. Campello
statistical and scientific database management 11

2
2018
Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

Ricardo J. G. B. Campello , Davoud Moulavi , Arthur Zimek , Jörg Sander
ACM Transactions on Knowledge Discovery From Data 10 ( 1) 5

561
2015
DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

Erich Schubert , Jörg Sander , Martin Ester , Hans Peter Kriegel
international conference on management of data 42 ( 3) 19

1,513
2017
Semi-supervised Density-Based Clustering

Levi Lelis , Jörg Sander
international conference on data mining 842 -847

122
2009
Multi-Aspect Review-Team Assignment using Latent Research Areas

Maryam Mirzaei , Jörg Sander , Eleni Stroulia
Information Processing and Management 56 ( 3) 858 -878

4
2019
PIST: An Efficient and Practical Indexing Technique for Historical Spatio-Temporal Point Data

Viorica Botea , Daniel Mallett , Mario A. Nascimento , Jörg Sander
Geoinformatica 12 ( 2) 143 -168

59
2008
OPTICS-OF: Identifying Local Outliers

Markus M. Breunig , Hans-Peter Kriegel , Raymond T. Ng , Jörg Sander
european conference on principles of data mining and knowledge discovery 262 -270

310
1999
On the internal evaluation of unsupervised outlier detection

Henrique O Marques , Ricardo JGB Campello , Arthur Zimek , Jörg Sander
statistical and scientific database management 7

17
2015
Clustering and knowledge discovery in spatial databases

Xiaowei Xu , Martin Ester , Hans-Peter Kriegel , Jörg Sander
Vistas in Astronomy 41 ( 3) 397 -403

12
1997
LOF: identifying density-based local outliers

Markus M. Breunig , Hans-Peter Kriegel , Raymond T. Ng , Jörg Sander
international conference on management of data 29 ( 2) 93 -104

13
2000
OPTICS: ordering points to identify the clustering structure

Mihael Ankerst , Markus M. Breunig , Hans-Peter Kriegel , Jörg Sander
international conference on management of data 28 ( 2) 49 -60

5,597
1999
Density-based clustering validation

Davoud Moulavi , Pablo A. Jaskowiak , Ricardo J. G. B. Campello , Arthur Zimek
siam international conference on data mining 839 -847

72
2014
Density‐based clustering

Hans‐Peter Kriegel , Peer Kröger , Jörg Sander , Arthur Zimek
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 1 ( 3) 231 -240

425
2011
Exploiting redundancy in sensor networks for energy efficient processing of spatiotemporal region queries

Alexandru Coman , Mario A. Nascimento , Jörg Sander
Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05 187 -194

19
2005
A Classification-Based Glioma Diffusion Model Using MRI Data

Marianne Morris , Russell Greiner , Jörg Sander , Albert Murtha
Advances in Artificial Intelligence 98 -109

3
2006
On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study

Guilherme O. Campos , Arthur Zimek , Jörg Sander , Ricardo J. G. B. Campello
Data Mining and Knowledge Discovery 30 ( 4) 891 -927

625
2016
A unified view of density-based methods for semi-supervised clustering and classification.

Jadson Castro Gertrudes , Arthur Zimek , Jörg Sander , Ricardo J. G. B. Campello
Data Mining and Knowledge Discovery 33 ( 6) 1894 -1952

12
2019
Correction to: A unified view of density-based methods for semi-supervised clustering and classification

Jadson Castro Gertrudes , Arthur Zimek , Jörg Sander , Ricardo J. G. B. Campello
Data Mining and Knowledge Discovery 34 ( 6) 1984 -1985

2020