Jörg Sander

机构: Professor, Computing Science, University of Alberta

每年引用次数

引用次数

引用: 67,584

H-指数: 50

I10-指数 : 92

出版物: 178

ACM Sigmod record

M Ankerst , MM Breunig , HP Kriegel , J Sander
New York: ACM 49 -60

33

1999

A nonparametric clustering algorithm for knowledge discovery in large spatial databases

X Xu , M Ester , HP Kriegel , J Sander
Proc. of the Intl. Conf. on Data Engineering (ICDE’98)

30

1998

Lof: identifying outliers in large dataset

Markus M Breunig , Hans-Peter Kriegel , RT Ng , J Sander
Proc. of ACM SIGMOD 29 ( 2) 93 -104

21

2000

Focused co-citation: Improving the retrieval of related pages on the web

Gabriela Moise , J Sander , D Rafiei
Proceedings of the 12th International world wide web Conference (Budapest, Hungary, 2003)

11

2004

A density-based algorithm for sparse representations

M Ester , H Kriegel , J Sander , X Xu
Proc. 2nd Int. Conf. Knowl. Discov. Data Mining 226 -231

10

1996

M Ester , HP Kriegel , J Sander , X Xu
A density-based algorithm for discovering clusters in large spatial databases with noise 226 -231

9

Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD’99)

M Ankerst , MM Breunig , HP Kriegel , J Sander
Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD99) 49 -60

8

1999

A density-based algorithm for discovering clusters in large

M Ester , HP Kriegel , J Sander , X Xu

8

1996

KDD'96: Proc. of the Second Int. Conf. on Knowledge Discovery and Data Mining

M Ester , HP Kriegel , J Sander , X Xu
Washington, DC: AAAI Press 226

8

1996

WIREs Data Mining Knowl

H Kriegel , P Kröger , J Sander , AJWIRDM Zimek
Discov 1 231 -231

7

2011

A density-based algorithm for discovering clusters in large spatial data sets with noise, 2nd Int

M Ester , H Kriegel , J Sander , X Xu
Conf. on Knowledge Discovery and Data Mining 226 -231

7

1996

In Encyclopedia of Machine Learning; Sammut, C., Webb, GI, Eds

J Sander , Density-Based Clustering
Springer US: Boston, MA 270 -273

6

2010

OPTICS: ordering points to identify the clustering structure. ACM SIGMOD Rec. 28, 49–60

M Ankerst , MM Breunig , HP Kriegel , J Sander

5

1999

Clustering for Mining in Large Spatial Databases, KI (Artificial Intelligence), Special Issue on Data Mining

M Ester , HP Kriegel , J Sander , X Xu
ScienTec Publishing 18 -24

5

1998

Density-based clustering in spatial databases

J Sander , M Ester , HP Kriegel , X Xu
Data Mining Knowledge Discovery’98

5

1998

M Ester , HP Kriegel , J Sander , X Xu
University of Munich

5

1996

LOF: identifying density-based local outliers. ACM SIGMOD Rec. 29 (2), 93–104 (2000)

MM Breunig , HP Kriegel , RT Ng , J Sander

5

for Discovering Clusters in Large Spatial Databases

M Ester , HP Kriegel , J Sander
Proc. of the Second International Conference on Data Mining KDD-96 226 -231

5

Identifying local outliers

MM Breunig , HP Kriegel , RT Ng , J Sander
Proceedings of PKDD'99, Prague, Czech Republic, Lecture Notes in Computer Science 262 -270

4

2000

Optics: Ordering points to identify the clustering structure, SIGMOD. 1999

M Breunig Ankerst , HP Kriegel , J Sander
Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives", Journal of Business Research

3

2009

Spatial and Temporal Data