Hans‐Peter Kriegel
About
In The Last Decade
Hans‐Peter Kriegel
213 papers receiving 36.8k citations
Hit Papers
Peers
Comparison fields: 5 of 229
- Artificial Intelligence 19.8k
- Signal Processing 13.1k
- Computer Vision and Pattern Recognition 8.9k
- Computer Networks and Communications 7.4k
- Information Systems 5.9k
Countries citing papers authored by Hans‐Peter Kriegel
This map shows the geographic impact of Hans‐Peter Kriegel'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‐Peter Kriegel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hans‐Peter Kriegel more than expected).
Fields of papers citing papers by Hans‐Peter Kriegel
This network shows the impact of papers produced by Hans‐Peter Kriegel. 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‐Peter Kriegel. The network helps show where Hans‐Peter Kriegel may publish in the future.
Co-authorship network of co-authors of Hans‐Peter Kriegel
This figure shows the co-authorship network connecting the top 25 collaborators of Hans‐Peter Kriegel. A scholar is included among the top collaborators of Hans‐Peter Kriegel 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‐Peter Kriegel. Hans‐Peter Kriegel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Three-Way Model for Collective Learning on Multi-Relational Data breakdown → | 905 |
| 2 | Generische Datenintegration zur semantischen Diagnoseunterstützung im Projekt THESEUS MEDICO. | 2 |
| 3 | Spiral Recurrent Neural Network for Online Learning | 9 |
| 4 | An Efficient Sampling Scheme For Comparison of Large Graphs. | 2 |
| 5 | Infinite hidden relational models | 80 |
| 6 | Measuring the Quality of Approximated Clusterings. | 2 |
| 7 | Der virtualle Prototyp: Datenbankunterstützung für CAD-Anwendungen. | 0 |
| 8 | Stochastic Driven Relational R-Tree | 1 |
| 9 | Incremental Clustering for Mining in a Data Warehousing Environment | 296 |
| 10 | Similarity Search in 3D Protein Databases | 21 |
| 11 | Improving Adaptable Similarity Query Processing by Using Approximations | 25 |
| 12 | Algorithms for characterization and trend detection in spatial databases | 69 |
| 13 | Efficient User-Adaptable Similarity Search in Large Multimedia Databases | 117 |
| 14 | Density-connected sets and their application for trend detection in spatial databases | 28 |
| 15 | A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise breakdown → | 810 |
| 16 | 'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets | 116 |
| 17 | Query Translation Supporting the Migration of Legacy Databases into Cooperative Information Systems | 4 |
| 18 | The Impact of Global Clustering on Spatial Database Systems | 21 |
| 19 | The Buddy-Tree: An Efficient and Robust Access Method for Spatial Data Base Systems | 109 |
| 20 | Techniques for Design and Implementation of Efficient Spatial Access Methods | 55 |
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.