Mihael Ankerst

6.9k citations
15 papers · 4.2k indexed · 2 hit papers · h-index 12

Mihael Ankerst

14 papers receiving 3.9k citations

Hit Papers

OPTICS908199920262008201750010001.5k2.0k2.5k

Peers

Mihael Ankerst
Comparison fields: 5 of 166
  • Signal Processing 1.5k
  • Artificial Intelligence 2.2k
  • Computer Vision and Pattern Recognition 1.3k
  • Transportation 395
  • Information Systems 745
Replace Pasi Fränti with:
Pasi Fränti Finland
Peer Kröger Germany
Markus Breunig Germany
Sanjay Chawla Australia
Arthur Zimek Germany
Mao Ye China
Delbert Dueck Canada
Juliana Freire United States
Jae-Gil Lee South Korea
David Arthur United States
Mihael Ankerst relative to Pasi Fränti Finland Pasi Fränti's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mihael Ankerst

Since Specialization
Citations

This map shows the geographic impact of Mihael Ankerst's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mihael Ankerst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mihael Ankerst more than expected).

Fields of papers citing papers by Mihael Ankerst

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mihael Ankerst. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mihael Ankerst. The network helps show where Mihael Ankerst may publish in the future.

Co-authorship network

The 14 scholars most cited alongside Mihael Ankerst, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mihael Ankerst Line = papers co-authored together Mihael Ankerst links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
Kooperatives Data Mining: Eine Integration von Data-Mining-Algorithmen und Visualisierungstechniken.
20040
2
DataJewel: Tightly integrating visualization with temporal data mining
20034
3 200217
4 200258
5 2002170
6
Visual Data Mining : Background, Techniques, and Drug Discovery Applications
20028
7
Human Involvement and Interactivity of the Next Generation’s Data Mining Tools
200111
8 2000116
9
Nearest neighbor classification in 3D protein databases.
199986
10 1999112
11 19992532
12 1999908
13
Improving Adaptable Similarity Query Processing by Using Approximations
199825
14 199826
15
'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets
1996116

About Mihael Ankerst

Mihael Ankerst is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Biophysics, having authored 15 papers that have together received 4.2k indexed citations. Recurring topics across this work include Data Management and Algorithms (8 papers), Data Visualization and Analytics (7 papers), Image Retrieval and Classification Techniques (4 papers), Advanced Database Systems and Queries (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Data Stream Mining Techniques (2 papers), Advanced Clustering Algorithms Research (2 papers) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (1.5k citations), Artificial Intelligence (2.2k citations) and Computer Vision and Pattern Recognition (1.3k citations). Mihael Ankerst has collaborated with scholars based in Germany, Australia and United States. Frequent co-authors include Hans‐Peter Kriegel, Jörg Sander, Markus Breunig, Daniel A. Keim, Martin Ester, Stefan Berchtold, H.-P. Kriegel, Thomas Seidl, Gabi Kastenmüller and Bernhard Braunmüller. Their work appears in journals such as ACM SIGMOD Record, IEEE Transactions on Knowledge and Data Engineering, KOPS (University of Konstanz), PubMed and ACM SIGKDD Explorations Newsletter.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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