Daniel A. Keim
Impact in
- Computer Vision and Pattern Recognition top 0.05%
- Data Visualization and Analytics
- Video Analysis and Summarization
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Signal Processing top 0.02%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
Papers in
-
- Data Visualization and Analytics 359
- Video Analysis and Summarization 96
- Image Retrieval and Classification Techniques 51
- Advanced Image and Video Retrieval Techniques 37
-
- Data Management and Algorithms 126
- Time Series Analysis and Forecasting 66
- Co-authors
- Alexander Hinneburg (17 shared papers)Stefan Berchtold (17 shared papers)Charų C. Aggarwal (2 shared papers)Hans‐Peter Kriegel (20 shared papers)Florian Mansmann (40 shared papers)Tobias Schreck (74 shared papers)Gennady Andrienko (25 shared papers)H.-P. Kriegel (8 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (43 papers)Computer Graphics Forum (35 papers)Information Visualization (15 papers)IEEE Computer Graphics and Applications (15 papers)ACM SIGMOD Record (7 papers)
- Partner nations
- GermanyUnited StatesAustria
In The Last Decade
Daniel A. Keim
546 papers receiving 19.9k citations
Daniel A. Keim's Hit Papers
Peers
Comparison fields: 5 of 211
- Computer Vision and Pattern Recognition 12.7k
- Signal Processing 6.4k
- Geography, Planning and Development 1.3k
- Artificial Intelligence 7.4k
- Computer Graphics and Computer-Aided Design 769
Countries citing papers authored by Daniel A. Keim
This map shows the geographic impact of Daniel A. Keim'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 Daniel A. Keim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel A. Keim more than expected).
Fields of papers citing papers by Daniel A. Keim
This network shows the impact of papers produced by Daniel A. Keim. 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 Daniel A. Keim. The network helps show where Daniel A. Keim may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel A. Keim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 568 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | On the Surprising Behavior of Distance Metrics in High Dimensional Space Hit paper breakdown → | 2001 | 1402 |
| 2 | Information visualization and visual data mining Hit paper breakdown → | 2002 | 1171 |
| 3 | An efficient approach to clustering in large multimedia databases with noise Hit paper breakdown → | 1998 | 930 |
| 4 | Visual Analytics: Definition, Process, and Challenges Hit paper breakdown → | 2008 | 801 |
| 5 | The X-tree: An Index Structure for High-Dimensional Data Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Hit paper breakdown → | 2002 | 736 |
| 6 | Searching in high-dimensional spaces Hit paper breakdown → | 2001 | 628 |
| 7 | 2008 | 407 | |
| 8 | What Is the Nearest Neighbor in High Dimensional Spaces | 2000 | 380 |
| 9 | 2000 | 320 | |
| 10 | 2007 | 319 | |
| 11 | 2005 | 295 | |
| 12 | 1997 | 292 | |
| 13 | 2006 | 287 | |
| 14 | Knowledge Generation Model for Visual Analytics Hit paper breakdown → | 2014 | 285 |
| 15 | 1996 | 277 | |
| 16 | Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering | 1999 | 258 |
| 17 | 2010 | 255 | |
| 18 | 2001 | 251 | |
| 19 | 1994 | 236 | |
| 20 | 2015 | 208 |
About Daniel A. Keim
Daniel A. Keim is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Statistical and Nonlinear Physics and Information Systems, having authored 568 papers that have together received 21.5k indexed citations. Recurring topics across this work include Data Visualization and Analytics (359 papers), Data Management and Algorithms (126 papers), Video Analysis and Summarization (96 papers), Time Series Analysis and Forecasting (66 papers), Complex Network Analysis Techniques (56 papers), Image Retrieval and Classification Techniques (51 papers), Advanced Text Analysis Techniques (47 papers) and Advanced Image and Video Retrieval Techniques (37 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (12.7k citations), Signal Processing (6.4k citations), Geography, Planning and Development (1.3k citations), Artificial Intelligence (7.4k citations) and Computer Graphics and Computer-Aided Design (769 citations). Daniel A. Keim has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Alexander Hinneburg, Stefan Berchtold, Charų C. Aggarwal, Hans‐Peter Kriegel, Florian Mansmann, Tobias Schreck, Gennady Andrienko, H.-P. Kriegel, Christian Böhm and Hartmut Ziegler. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Information Visualization, IEEE Computer Graphics and Applications and ACM SIGMOD Record.
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.