Arno Siebes

501 total citations
37 papers, 148 citations indexed

About

Arno Siebes is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Arno Siebes has authored 37 papers receiving a total of 148 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 11 papers in Computer Networks and Communications and 11 papers in Signal Processing. Recurrent topics in Arno Siebes's work include Advanced Database Systems and Queries (11 papers), Data Mining Algorithms and Applications (6 papers) and Data Management and Algorithms (6 papers). Arno Siebes is often cited by papers focused on Advanced Database Systems and Queries (11 papers), Data Mining Algorithms and Applications (6 papers) and Data Management and Algorithms (6 papers). Arno Siebes collaborates with scholars based in Netherlands, United Kingdom and Canada. Arno Siebes's co-authors include Zbigniew R. Struzik, Ad Feelders, Michael R. Berthold, Wouter Duivesteijn, Antti Ukkonen, Robert C. Glen, Katharina Morik, Jean‐François Boulicaut, Martin Kersten and Robert Castelo and has published in prestigious journals such as Expert Systems with Applications, Computer Methods and Programs in Biomedicine and ACM Transactions on Information Systems.

In The Last Decade

Arno Siebes

32 papers receiving 130 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arno Siebes Netherlands 7 68 41 39 25 24 37 148
Ron Musick United States 7 70 1.0× 46 1.1× 26 0.7× 19 0.8× 7 0.3× 17 159
Yannick Toussaint France 7 103 1.5× 16 0.4× 59 1.5× 30 1.2× 51 2.1× 44 152
Werner Emde Germany 6 147 2.2× 40 1.0× 78 2.0× 12 0.5× 38 1.6× 11 207
B. McKinnon United Kingdom 2 86 1.3× 53 1.3× 74 1.9× 20 0.8× 45 1.9× 3 174
Yanbin Wang China 10 63 0.9× 40 1.0× 57 1.5× 69 2.8× 15 0.6× 22 216
Jørgen Fischer Nilsson Denmark 6 112 1.6× 15 0.4× 43 1.1× 14 0.6× 27 1.1× 41 156
Luke Mathieson Australia 7 25 0.4× 18 0.4× 25 0.6× 29 1.2× 64 2.7× 28 165
Elias Zavitsanos Greece 7 100 1.5× 9 0.2× 43 1.1× 17 0.7× 7 0.3× 15 133
Oliver Ray United Kingdom 7 158 2.3× 14 0.3× 27 0.7× 35 1.4× 32 1.3× 32 204
Frithjof Dau Australia 6 78 1.1× 11 0.3× 38 1.0× 17 0.7× 30 1.3× 17 119

Countries citing papers authored by Arno Siebes

Since Specialization
Citations

This map shows the geographic impact of Arno Siebes'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 Arno Siebes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arno Siebes more than expected).

Fields of papers citing papers by Arno Siebes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arno Siebes. 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 Arno Siebes. The network helps show where Arno Siebes may publish in the future.

Co-authorship network of co-authors of Arno Siebes

This figure shows the co-authorship network connecting the top 25 collaborators of Arno Siebes. A scholar is included among the top collaborators of Arno Siebes 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 Arno Siebes. Arno Siebes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Heijden, P.G.M. van der, et al.. (2025). Using Chao’s Estimator as a Stopping Criterion for Technology-Assisted Review. ACM Transactions on Information Systems. 43(3). 1–51. 2 indexed citations
2.
Siebes, Arno, et al.. (2025). TransCORALNet: A two-stream transformer CORAL networks for supply chain credit assessment cold start. Expert Systems with Applications. 282. 127581–127581. 1 indexed citations
3.
Liang, David, Animesh Kumar Paul, Daniala L. Weir, et al.. (2025). Methods in dynamic treatment regimens using observational healthcare data: A systematic review. Computer Methods and Programs in Biomedicine. 263. 108658–108658.
4.
Alderliesten, Thomas, et al.. (2023). Continuous Data-Driven Monitoring in Critical Congenital Heart Disease: Clinical Deterioration Model Development. JMIR Cardio. 7. e45190–e45190. 2 indexed citations
5.
Velden, Lieke M. van der, René H. Medema, Arno Siebes, et al.. (2020). Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening. SLAS DISCOVERY. 25(6). 655–664. 15 indexed citations
6.
Siebes, Arno. (2018). Data science as a language: challenges for computer science—a position paper. International Journal of Data Science and Analytics. 6(3). 177–187. 6 indexed citations
7.
Siebes, Arno, et al.. (2014). Characterising Seismic Data.. Utrecht University Repository (Utrecht University). 884–892. 1 indexed citations
8.
Siebes, Arno, et al.. (2011). A Structure Function for Transaction Data. 558–569. 5 indexed citations
9.
Hussong, René, Andreas Tholey, Andreas Hildebrandt, et al.. (2007). Efficient Analysis of Mass Spectrometry Data Using the Isotope Wavelet. AIP conference proceedings. 940. 139–149. 10 indexed citations
10.
Morik, Katharina, Jean‐François Boulicaut, & Arno Siebes. (2005). Local Pattern Detection: International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence). Springer eBooks. 5 indexed citations
11.
Goethals, Bart & Arno Siebes. (2005). Knowledge Discovery in Inductive Databases: Third International Workshop, KDID 2004, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers (Lecture Notes in Computer Science). Springer eBooks. 1 indexed citations
12.
Siebes, Arno, et al.. (1996). A framework for query optimization to support data mining. Department of Computer Science [CS]. 1–14.
13.
Siebes, Arno, et al.. (1996). DEGAS : a temporal active data model based on object autonomy. Department of Computer Science [CS]. 1–52. 2 indexed citations
14.
Siebes, Arno, et al.. (1996). Deductive Databases: Challenges, Opportunities and Future Directions (Panel Discussion). 225–229. 1 indexed citations
15.
Siebes, Arno. (1995). Data surveying foundations of an inductive query language. Knowledge Discovery and Data Mining. 269–274. 15 indexed citations
16.
Siebes, Arno, et al.. (1995). A data model for autonomous objects. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–23. 2 indexed citations
17.
Siebes, Arno. (1994). Homogeneous discoveries contain no surprises: inferring risk-profiles from large databases. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–108. 6 indexed citations
18.
Siebes, Arno, et al.. (1993). Schema refinement and schema integration in object-oriented databases.. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–19. 2 indexed citations
19.
Siebes, Arno, et al.. (1992). Towards a design theory for Database triggers.. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 338–344. 1 indexed citations
20.
Kersten, Martin, et al.. (1988). Using a graph rewriting system for databases. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–13. 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.

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