M. Ankerst

发表

OPTICS: ordering points to identify the clustering structure

M. Ankerst, M. Breunig, H. Kriegel, 1999, ACM SIGMOD Conference.

Video Indexing

Marcel Worring, Marta Mattoso, Yannis Sismanis, 2009, Encyclopedia of Database Systems.

1 VISUAL DATA MINING AND PIXEL-ORIENTED VISUALIZATION

M. Ankerst, 2022 .

Visual Data Analysis

Marcel Worring, Marta Mattoso, Yannis Sismanis, 2009, Encyclopedia of Database Systems.

Visual Similarity

Cees G. M. Snoek, Heng Tao Shen, Yannis Sismanis, 2009, Encyclopedia of Database Systems.

Perception-Based Classification

Hans-Peter Kriegel, Martin Ester, Mihael Ankerst, 1999, Informatica.

Visual Data Mining

Mihael Ankerst, M. Ankerst, C. Elsen, 2001, Encyclopedia of GIS.

Visual Classification

Mihael Ankerst, M. Ankerst, 2009, Encyclopedia of Database Systems.

Circle seg-ments: a technique for visual exploring large multidi-mensional data sets

Daniel A. Keim, Mihael Ankerst, H.-P. Kriegel, 1996 .

Visual data mining: background

Daniel A. Keim, Mihael Ankerst, Georges G. Grinstein, 2002 .

Visual Data-Mining Techniques An earlier version of this paper with focus on visualization techniques and their classification has been published in Visual Data Analysis: An Introduction (D. Hand and M. Berthold, Eds.)

Daniel A. Keim, Mihael Ankerst, Mike Sips, 2005, The Visualization Handbook.

Visual data mining: background

Daniel A. Keim, Mihael Ankerst, Georges G. Grinstein, 2002 .

Recursive pattern: a technique for visualizing very large amounts of data

Hans-Peter Kriegel, Daniel A. Keim, Mihael Ankerst, 1995, Proceedings Visualization '95.

OPTICS: ordering points to identify the clustering structure

Hans-Peter Kriegel, Mihael Ankerst, Markus M. Breunig, 1999, SIGMOD '99.

3D Shape Histograms for Similarity Search and Classification in Spatial Databases

Hans-Peter Kriegel, Thomas Seidl, Mihael Ankerst, 1999, SSD.

Stefan Berchtold, Daniel A. Keim, Mihael Ankerst, 1998, Proceedings IEEE Symposium on Information Visualization (Cat. No.98TB100258).

Human Involvement and Interactivity of the Next Generation’s Data Mining Tools

Mihael Ankerst, M. Ankerst, 2001 .

Ordering The Database With Respect To The Clustering Structure 3

M. Ankerst, M. Breunig, H. Kriegel, 1999 .

Nearest Neighbor Classification in 3D Protein Databases

Hans-Peter Kriegel, Thomas Seidl, Mihael Ankerst, 1999, ISMB.

A Multistep Approach for Shape Similarity Search in Image Databases

Hans-Peter Kriegel, Mihael Ankerst, Thomas Seidl, 1998, IEEE Trans. Knowl. Data Eng..

Improving Adaptable Similarity Query Processing by Using Approximations

Hans-Peter Kriegel, Thomas Seidl, Mihael Ankerst, 1998, VLDB.

Towards an effective cooperation of the user and the computer for classification

Hans-Peter Kriegel, Martin Ester, Mihael Ankerst, 2000, KDD '00.

Visual classification: an interactive approach to decision tree construction

Hans-Peter Kriegel, Martin Ester, Mihael Ankerst, 1999, KDD '99.

DataJewel: Integrating Visualization with Temporal Data Mining

Changzhou Wang, Mihael Ankerst, Anne Kao, 2008, Visual Data Mining.

'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets

Hans-Peter Kriegel, Daniel A. Keim, Mihael Ankerst, 1996 .

Report on the SIGKDD-2002 panel the perfect data mining tool: interactive or automated?

Mihael Ankerst, M. Ankerst, 2002, SKDD.

Towards an Effective Cooperation of the Computer and the User for Classification

Hans-Peter Kriegel, Martin Ester, Mihael Ankerst, 2000, KDD 2000.

Visual data mining

Sunita Kanaujiya, M. Ankerst, Sunita Kanaujiya, 2001 .

43 Visual Data-Mining Techniques*

Daniel A. Keim, Mihael Ankerst, Mike Sips, 2004 .

Visual data mining: background

M. Ankerst, D. Keim, G. Grinstein, 2002 .