Erik Faessler
About
In The Last Decade
Erik Faessler
16 papers receiving 161 citations
Peers
Comparison fields: 5 of 44
- Molecular Biology 152
- Artificial Intelligence 87
- Cell Biology 12
- Information Systems 8
- Physiology 7
Countries citing papers authored by Erik Faessler
This map shows the geographic impact of Erik Faessler'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 Erik Faessler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erik Faessler more than expected).
Fields of papers citing papers by Erik Faessler
This network shows the impact of papers produced by Erik Faessler. 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 Erik Faessler. The network helps show where Erik Faessler may publish in the future.
Co-authorship network of co-authors of Erik Faessler
This figure shows the co-authorship network connecting the top 25 collaborators of Erik Faessler. A scholar is included among the top collaborators of Erik Faessler 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 Erik Faessler. Erik Faessler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 4 | |
| 3 | JULIE Lab & Med Uni Graz @ TREC 2019 Precision Medicine Track. | 3 |
| 4 | 55 | |
| 5 | HPI-DHC at TREC 2018 Precision Medicine Track. | 6 |
| 6 | 1 | |
| 7 | 5 | |
| 8 | Integrated Semantic Search on Structured and Unstructured Data in the ADOnIS System. | 5 |
| 9 | UIMA-Based JCoRe 2.0 Goes GitHub and Maven Central ― State-of-the-Art Software Resource Engineering and Distribution of NLP Pipelines. | 6 |
| 10 | 8 | |
| 11 | Disclose Models, Hide the Data - How to Make Use of Confidential Corpora without Seeing Sensitive Raw Data | 3 |
| 12 | Iterative Refinement and Quality Checking of Annotation Guidelines ― How to Deal Effectively with Semantically Sloppy Named Entity Types, such as Pathological Phenomena | 1 |
| 13 | Active Learning-based corpus annotation--the PathoJen experience. | 6 |
| 14 | 13 | |
| 15 | A Proposal for a Configurable Silver Standard | 3 |
| 16 | 52 |
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.