Hans Hermann Bock
- Artificial Intelligence top 5%
- Statistics and Probability top 5%
- Signal Processing top 10%
- Computational Theory and Mathematics top 10%
- Information Systems top 10%
- Co-authors
- Edwin DidayMaurizio VichiPeter Ihm
- Topics
- Neural Networks and Applications (2 papers)Sensory Analysis and Statistical Methods (1 paper)Time Series Analysis and Forecasting (1 paper)
In The Last Decade
Hans Hermann Bock
9 papers receiving 338 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 227
- Statistics and Probability 89
- Signal Processing 73
- Computational Theory and Mathematics 62
- Information Systems 47
Countries citing papers authored by Hans Hermann Bock
This map shows the geographic impact of Hans Hermann Bock'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 Hans Hermann Bock with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hans Hermann Bock more than expected).
Fields of papers citing papers by Hans Hermann Bock
This network shows the impact of papers produced by Hans Hermann Bock. 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 Hans Hermann Bock. The network helps show where Hans Hermann Bock may publish in the future.
Co-authorship network of co-authors of Hans Hermann Bock
This figure shows the co-authorship network connecting the top 25 collaborators of Hans Hermann Bock. A scholar is included among the top collaborators of Hans Hermann Bock 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 Hans Hermann Bock. Hans Hermann Bock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data | 312 |
| 3 | 9 | |
| 4 | Classification, data analysis, and knowledge organization models and methods with applications : proceedings of the 14th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Marburg, March 12-14, 1990 | 1 |
| 5 | Classification and related methods of data analysis : proceedings of the First Conference of the International Federation of Classification Societies (IFCS), Technical University of Aachen, F.R.G., 29 June - 1 July, 1987 | 8 |
| 6 | 5 | |
| 7 | 15 | |
| 8 | Automatische Klassifikation. Theoretische und praktische Methoden zur Gruppierung und Strukturierung von Daten | 9 |
| 9 | 7 |
About Hans Hermann Bock
Hans Hermann Bock is a scholar working on Statistics and Probability, Artificial Intelligence and Signal Processing, having authored 9 papers that have together received 369 indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Sensory Analysis and Statistical Methods (1 paper) and Time Series Analysis and Forecasting (1 paper). The work is most often cited by research in Statistics and Probability (89 citations), Artificial Intelligence (227 citations) and Signal Processing (73 citations). Hans Hermann Bock has collaborated with scholars based in Germany and Italy. Frequent co-authors include Edwin Diday, Maurizio Vichi and Peter Ihm. Their work appears in journals such as Computational Statistics & Data Analysis, International Statistical Review and OR Spectrum.
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.