Ines Färber
Impact in
-
- Complex Network Analysis Techniques
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Anomaly Detection Techniques and Applications
- Advanced Graph Neural Networks
Papers in
-
- Advanced Clustering Algorithms Research 14
-
- Biometric Identification and Security 3
- Data Management and Algorithms 1
- Co-authors
- Thomas Seidl (19 shared papers)Stephan Günnemann (13 shared papers)Brigitte Boden (4 shared papers)Emmanuel Müller (4 shared papers)Tobias Schreck (3 shared papers)Sebastian Raubach (1 shared paper)Daniel A. Keim (3 shared papers)Andrada Tatu (2 shared papers)
- Journals
- Proceedings of the VLDB Endowment (1 paper)Knowledge and Information Systems (1 paper)Lecture notes in computer science (3 papers)RWTH Publications (RWTH Aachen) (1 paper)IEEE Conference on Visual Analytics Science and Technology (VAST) (1 paper)
- Partner nations
- GermanyUnited StatesNorway
In The Last Decade
Ines Färber
20 papers receiving 544 citations
Peers
Comparison fields: 5 of 38
- Statistical and Nonlinear Physics 149
- Artificial Intelligence 289
- Computer Vision and Pattern Recognition 151
- Signal Processing 22
- Information Systems 56
Countries citing papers authored by Ines Färber
This map shows the geographic impact of Ines Färber'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 Ines Färber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ines Färber more than expected).
Fields of papers citing papers by Ines Färber
This network shows the impact of papers produced by Ines Färber. 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 Ines Färber. The network helps show where Ines Färber may publish in the future.
Co-authors
The 24 scholars most cited alongside Ines Färber, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 92 | |
| 2 | On Using Class-Labels in Evaluation of Clusterings | 2010 | 83 |
| 3 | 2012 | 75 | |
| 4 | 2012 | 48 | |
| 5 | 2013 | 46 | |
| 6 | 2013 | 43 | |
| 7 | 2011 | 35 | |
| 8 | 2009 | 31 | |
| 9 | 2013 | 27 | |
| 10 | 2012 | 23 | |
| 11 | 2014 | 18 | |
| 12 | 2012 | 10 | |
| 13 | 2015 | 8 | |
| 14 | 2010 | 4 | |
| 15 | 2010 | 4 | |
| 16 | 2011 | 4 | |
| 17 | Visual Quality Assessment of Subspace Clusterings | 2016 | 3 |
| 18 | Efficient database techniques for identification with fuzzy vault templates | 2011 | 2 |
| 19 | Filtertechniken für geschützte biometrische Datenbanken. | 2011 | 2 |
| 20 | Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors | 2013 | 1 |
About Ines Färber
Ines Färber is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Information Systems and Statistical and Nonlinear Physics, having authored 20 papers that have together received 559 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (14 papers), Biometric Identification and Security (3 papers), Data Mining Algorithms and Applications (3 papers), Graph Theory and Algorithms (3 papers), Data Visualization and Analytics (2 papers), Data Management and Algorithms (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (149 citations), Artificial Intelligence (289 citations), Computer Vision and Pattern Recognition (151 citations), Signal Processing (22 citations) and Information Systems (56 citations). Ines Färber has collaborated with scholars based in Germany, United States and Norway. Frequent co-authors include Thomas Seidl, Stephan Günnemann, Brigitte Boden, Emmanuel Müller, Tobias Schreck, Sebastian Raubach, Daniel A. Keim, Andrada Tatu, Enrico Bertini and Peer Kröger. Their work appears in journals such as Proceedings of the VLDB Endowment, Knowledge and Information Systems, Lecture notes in computer science, RWTH Publications (RWTH Aachen) and IEEE Conference on Visual Analytics Science and Technology (VAST).
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.