Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
OPTICS
19992.5k citationsMihael Ankerst, Markus Breunig et al.ACM SIGMOD Recordprofile →
OPTICS
1999908 citationsMihael Ankerst, Markus Breunig et al.profile →
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).
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 of co-authors of Mihael Ankerst
This figure shows the co-authorship network connecting the top 25 collaborators of Mihael Ankerst.
A scholar is included among the top collaborators of Mihael Ankerst based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Mihael Ankerst. Mihael Ankerst is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
15 of 15 papers shown
#
Work
Indexed citations
1
Kooperatives Data Mining: Eine Integration von Data-Mining-Algorithmen und Visualisierungstechniken.
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.