Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Modeling aspects of the language of life through transfer-learning protein sequences
Countries citing papers authored by Florian Matthes
Since
Specialization
Citations
This map shows the geographic impact of Florian Matthes'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 Florian Matthes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Matthes more than expected).
This network shows the impact of papers produced by Florian Matthes. 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 Florian Matthes. The network helps show where Florian Matthes may publish in the future.
Co-authorship network of co-authors of Florian Matthes
This figure shows the co-authorship network connecting the top 25 collaborators of Florian Matthes.
A scholar is included among the top collaborators of Florian Matthes 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 Florian Matthes. Florian Matthes is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Matthes, Florian, et al.. (2020). Towards a Privacy-Enhancing Tool Based on De- Identification Methods. Journal of the Association for Information Systems.1 indexed citations
11.
Matthes, Florian, et al.. (2019). "Appropriate Technical and Organizational Measures": Identifying Privacy Engineering Approaches to Meet GDPR Requirements.. Journal of the Association for Information Systems.6 indexed citations
12.
Waltl, Bernhard, et al.. (2018). Named Entity Recognition, Extraction, and Linking in German Legal Contracts.7 indexed citations
13.
Matthes, Florian, et al.. (2018). Towards an Ontology-Based Information System for Smart City Ecosystems. Journal of the Association for Information Systems.1 indexed citations
14.
Waltl, Bernhard, et al.. (2017). Automated Extraction of Semantic Information from German Legal Documents.4 indexed citations
15.
Roth, Sascha & Florian Matthes. (2013). Future Research Topics in Enterprise Architectures Evolution Analysis.. 201–206.1 indexed citations
16.
Freitag, Andreas, et al.. (2012). DECISION SUPPORT FOR SELECTING AN APPLICATION LANDSCAPE INTEGRATION STRATEGY IN MERGERS AND ACQUISITIONS. Journal of the Association for Information Systems. 88.4 indexed citations
17.
Buschle, Markus, et al.. (2012). Automating enterprise architecture documentation using an enterprise service bus. Americas Conference on Information Systems. 4213–4226.25 indexed citations
18.
Buckl, Sabine, Alexander M. Ernst, Florian Matthes, & Christian M. Schweda. (2009). Enterprise Architecture Management Patterns for Enterprise Architecture Visioning. European Conference on Pattern Languages of Programs.4 indexed citations
19.
Kemper, Alfons, Donald Kossmann, & Florian Matthes. (1998). SAP R/3: A Database Application System (Tutorial).. International Conference on Management of Data. 499.6 indexed citations
20.
Matthes, Florian & Joachim W. Schmidt. (1989). The type system of DBPL. 219–225.7 indexed citations
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.