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.
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
2023205 citationsMeike Nauta, Jan Trienes et al.ACM Computing Surveysprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Maurice van Keulen
Since
Specialization
Citations
This map shows the geographic impact of Maurice van Keulen'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 Maurice van Keulen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maurice van Keulen more than expected).
Fields of papers citing papers by Maurice van Keulen
This network shows the impact of papers produced by Maurice van Keulen. 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 Maurice van Keulen. The network helps show where Maurice van Keulen may publish in the future.
Co-authorship network of co-authors of Maurice van Keulen
This figure shows the co-authorship network connecting the top 25 collaborators of Maurice van Keulen.
A scholar is included among the top collaborators of Maurice van Keulen 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 Maurice van Keulen. Maurice van Keulen is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Goseling, Jasper, et al.. (2021). Autoencoder-based cleaning in probabilistic databases. University of Twente Research Information.1 indexed citations
5.
Ceravolo, Paolo, Maurice van Keulen, & Kilian Stoffel. (2017). Proceedings of the 7th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2017). Data Archiving and Networked Services (DANS). 2016.7 indexed citations
6.
Huisman, Marieke, et al.. (2014). Towards Online and Transactional Relational Schema Transformations. University of Twente Research Information. 2(7683). 1143–4.
Keulen, Maurice van, et al.. (2011). Handling uncertainty in information extraction. University of Twente Research Information. 109–112.4 indexed citations
9.
Keulen, Maurice van, et al.. (2010). Run-time Optimization for Pipelined Systems.
10.
Keulen, Maurice van, et al.. (2010). Storing and Querying Probabilistic XML Using a Probabilistic Relational DBMS. University of Twente Research Information. 35–49.8 indexed citations
11.
Keulen, Maurice van, et al.. (2009). Duplicate Detection in Probabilistic Data. University of Twente Research Information.1 indexed citations
12.
Keulen, Maurice van & Ander de Keijzer. (2008). Qualitative Effects of Knowledge Rules in Probabilistic Data Integration. University of Twente Research Information.1 indexed citations
13.
Franqueira, Virginia N. L. & Maurice van Keulen. (2008). Analysis of the NIST database towards the composition of vulnerabilities in attack scenarios. Kent Academic Repository (University of Kent).5 indexed citations
14.
Keijzer, Ander de & Maurice van Keulen. (2007). User Feedback in Probabilistic XML. University of Twente Research Information.3 indexed citations
15.
Boncz, Peter, Torsten Grust, Maurice van Keulen, et al.. (2005). Pathfinder: XQuery---the relational way. University of Twente Research Information. 1322–1325.21 indexed citations
Keulen, Maurice van. (2004). Relational Approach to Logical Query Optimization of XPath. University of Twente Research Information. 57–63.1 indexed citations
18.
Keulen, Maurice van, et al.. (2002). Moa: extensibility and efficiency in querying nested data. Data Archiving and Networked Services (DANS). 1–31.3 indexed citations
19.
Keulen, Maurice van, et al.. (1998). Trends in tools voor gegevensmodellering. University of Twente Research Information. 40. 8–12.1 indexed citations
20.
Flokstra, Jan, et al.. (1994). Object-Oriented Programming. Lecture notes in computer science.3 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.