Margareta Ackerman

2.0k citations
29 papers · 486 · h-index 11

Impact in

Papers in

Margareta Ackerman

26 papers receiving 460 citations

Peers

Margareta Ackerman
Comparison fields: 5 of 132
  • Signal Processing 102
  • Artificial Intelligence 255
  • Statistical and Nonlinear Physics 83
  • Computer Vision and Pattern Recognition 79
  • Health Informatics 5
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Alneu de Andrade Lopes Brazil
O‐Joun Lee South Korea
Lucas Vendramin Brazil
Sebastian Tschiatschek Austria
Graham Wills United States
Jinchao Ji China
Jacob Kogan United States
Yanyan Zhang China
Krishna Kumar Mohbey India
Zhaoyun Ding China
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Citations per year

Countries citing papers authored by Margareta Ackerman

Since Specialization
Citations

This map shows the geographic impact of Margareta Ackerman'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 Margareta Ackerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Margareta Ackerman more than expected).

Fields of papers citing papers by Margareta Ackerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margareta Ackerman. 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 Margareta Ackerman. The network helps show where Margareta Ackerman may publish in the future.

Co-authors

The 24 scholars most cited alongside Margareta Ackerman, 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 Margareta Ackerman Line = papers co-authored together Margareta Ackerman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018148
2
Measures of Clustering Quality: A Working Set of Axioms for Clustering
200876
3
Clusterability: A Theoretical Study
200945
4
A characterization of linkage-based hierarchical clustering
201628
5
Towards Property-Based Classification of Clustering Paradigms
201024
6
Human Cluster Evaluation and Formal Quality Measures: A Comparative Study
201224
7
Characterization of Linkage-based Clustering
201022
8 201918
9 201313
10 202112
11 202212
12 200910
13 20119
14 20149
15 20168
16 20187
17 20164
18
Interactive Augmented Reality for Dance.
20163
19 20143
20
Co-Creative Conceptual Art.
20182

About Margareta Ackerman

Margareta Ackerman is a scholar working on Artificial Intelligence, Signal Processing, Statistical and Nonlinear Physics, Information Systems and Computational Theory and Mathematics, having authored 29 papers that have together received 486 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (14 papers), Data Management and Algorithms (10 papers), Complex Network Analysis Techniques (7 papers), Data Mining Algorithms and Applications (4 papers), Bayesian Methods and Mixture Models (3 papers), Genomics and Phylogenetic Studies (2 papers), Human Motion and Animation (2 papers) and Genetic diversity and population structure (2 papers). The work is most often cited by research in Signal Processing (102 citations), Artificial Intelligence (255 citations), Statistical and Nonlinear Physics (83 citations), Computer Vision and Pattern Recognition (79 citations) and Health Informatics (5 citations). Margareta Ackerman has collaborated with scholars based in United States, Canada and Portugal. Frequent co-authors include Shai Ben-David, Naomi C. Brownstein, David Loker, Virginia R. de, Joshua M. Lewis, Simina Brânzei, Jeffrey Shallit, Sanjoy Dasgupta, Alejandro López-Ortíz and Ricardo Baeza‐Yates. Their work appears in journals such as Pattern Recognition, Autonomous Agents and Multi-Agent Systems, Theoretical Computer Science, Cognitive Systems Research and Journal of Machine Learning Research.

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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