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.
Combining global optimization with local selection for efficient QoS-aware service composition
2009437 citationsMohammad Alrifai, Thomas Risseprofile →
Selecting skyline services for QoS-based web service composition
2010337 citationsMohammad Alrifai, Thomas Risse et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Thomas Risse'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 Thomas Risse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Risse more than expected).
This network shows the impact of papers produced by Thomas Risse. 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 Thomas Risse. The network helps show where Thomas Risse may publish in the future.
Co-authorship network of co-authors of Thomas Risse
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Risse.
A scholar is included among the top collaborators of Thomas Risse 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 Thomas Risse. Thomas Risse is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tahmasebi, Nina, et al.. (2013). BlogNEER: Applying Named Entity Evolution Recognition on the Blogosphere. Chalmers Publication Library (Chalmers University of Technology). 1091. 28–39.3 indexed citations
6.
Tahmasebi, Nina & Thomas Risse. (2013). The Role of Language Evolution in Digital Archives. Chalmers Publication Library (Chalmers University of Technology). 16–27.1 indexed citations
Tahmasebi, Nina, et al.. (2012). NEER: An Unsupervised Method for Named Entity Evolution Recognition. Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt). 2553–2568.25 indexed citations
9.
Risse, Thomas, et al.. (2012). Grundbegriffe der Governanceforschung. Refubium (Universitätsbibliothek der Freien Universität Berlin).3 indexed citations
Tahmasebi, Nina, Sukriti Ramesh, & Thomas Risse. (2009). First Results on Detecting Term Evolutions. The Library of Electronic Cyprus Thematic Organized Collections (LYKYTHOS) (University of Cyprus).3 indexed citations
14.
Alrifai, Mohammad & Thomas Risse. (2009). Combining global optimization with local selection for efficient QoS-aware service composition. 881–890.437 indexed citations breakdown →
Hemmje, Matthias, Claudia Niederée, & Thomas Risse. (2005). From Integrated Publication and Information Systems to Information and Knowledge Environments: Essays Dedicated to Erich J. Neuhold on the Occasion o ... Birthday (Lecture Notes in Computer Science). Springer eBooks.1 indexed citations
18.
Risse, Thomas, Andreas Wombacher, Mike Surridge, Stephen Taylor, & Karl Aberer. (2001). Online Scheduling in Distributed Message Converter Systems. ePrints Soton (University of Southampton). 177–184.3 indexed citations
19.
Risse, Thomas, Andreas Wombacher, & Karl Aberer. (2000). Efficient Processing of Voluminous EDI Documents. Journal of the Association for Information Systems. 343–350.3 indexed citations
20.
Brause, Rüdiger, et al.. (1983). Softwarekonzepte des fehlertoleranten Arbeitsplatzrechners ATTEMPTO. 328–341.1 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.