Siegfried Nijssen

3.5k citations
73 papers · 1.6k indexed · h-index 20
Topics
Data Mining Algorithms and Applications (46 papers)Rough Sets and Fuzzy Logic (22 papers)Advanced Database Systems and Queries (17 papers)

In The Last Decade

Siegfried Nijssen

71 papers receiving 1.4k citations

Peers

Siegfried Nijssen
Comparison fields: 5 of 138
  • Information Systems 777
  • Artificial Intelligence 683
  • Computational Theory and Mathematics 500
  • Signal Processing 347
  • Computer Networks and Communications 327
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Countries citing papers authored by Siegfried Nijssen

Since Specialization
Citations

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

Fields of papers citing papers by Siegfried Nijssen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siegfried Nijssen

This figure shows the co-authorship network connecting the top 25 collaborators of Siegfried Nijssen. A scholar is included among the top collaborators of Siegfried Nijssen 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 Siegfried Nijssen. Siegfried Nijssen 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
#WorkIndexed citations
1 78
2 10
3 1
4 1
5 1
6 14
7
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013
2
8
MiningZinc: a modeling language for constraint-based mining
9
9
Machine learning and knowledge discovery in databases, European Conference, ECML PKDD 2013, Proceedings, Part III
4
10 65
11 3
12
Data mining, interactive semantic structuring, and collaboration: a diversity-aware method for sense-making in search
2
13
Induction of node label controlled graph grammar rules
5
14
General graph refinement with polynomial delay
2
15
What is frequent in a single graph
3
16
Frequent subgraph miners: runtimes don't say everything
19
17
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
3
18 150
19
Ideal refinement of Datalog clauses using primary keys
1
20
Faster association rules for multiple relations
43

About Siegfried Nijssen

Siegfried Nijssen is a scholar working on Information Systems, Signal Processing and Computational Theory and Mathematics, having authored 73 papers that have together received 1.6k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (46 papers), Rough Sets and Fuzzy Logic (22 papers) and Advanced Database Systems and Queries (17 papers). The work is most often cited by research in Information Systems (777 citations), Signal Processing (347 citations) and Computational Theory and Mathematics (500 citations). Siegfried Nijssen has collaborated with scholars based in Belgium, Netherlands and United States. Frequent co-authors include Joost N. Kok, Luc De Raedt, Tias Guns, Hendrik Blockeel, Richard R. Muntz, Yün Chi, Kristian Kersting, Pierre Schaus, Filip Železný and Thomas Bäck. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Artificial Intelligence.

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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