Jan Struyf

2.4k citations
42 papers · 1.0k · h-index 11

Impact in

    • Text and Document Classification Technologies
    • Machine Learning and Data Classification
    • Data Mining Algorithms and Applications
    • Spam and Phishing Detection

Papers in

Jan Struyf

29 papers receiving 947 citations

Peers

Jan Struyf
Comparison fields: 5 of 116
  • Artificial Intelligence 663
  • Information Systems 231
  • Computer Vision and Pattern Recognition 177
  • Computational Theory and Mathematics 116
  • Molecular Biology 329
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Countries citing papers authored by Jan Struyf

Since Specialization
Citations

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

Fields of papers citing papers by Jan Struyf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jan Struyf, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Struyf Line = papers co-authored together Jan Struyf links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008434
2 2012175
3 2010138
4
Hierarchical multi-classification
200246
5 200537
6 200833
7
Query transformations for improving the efficiency of ilp systems
200324
8
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
200821
9 201019
10
Decision trees for hierarchical multilabel classification: A case study in functional genomics
200613
11 201010
12
Predicting gene function in S. cerevisiae and A. thaliana using hierarchical multi-label decision tree ensembles
20087
13
Deriving biased classifiers for better ROC performance
20015
14
Learning Ground CP-logic Theories by means of Bayesian Network Techniques
20085
15
First-Order Bayes-Ball for CP-Logic
20095
16
Knowledge discovery in inductive databases : 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006 : revised selected and invited papers
20074
17 20043
18
Constrained clustering of gene expression profiles
20053
19
Query optimization: Combining query packs and the once-tranformation
20032
20
First order models for the predictive toxicology challenge
20012

About Jan Struyf

Jan Struyf is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Computer Networks and Communications and Computational Theory and Mathematics, having authored 42 papers that have together received 1.0k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (12 papers), Bayesian Modeling and Causal Inference (6 papers), Advanced Database Systems and Queries (5 papers), Machine Learning in Bioinformatics (5 papers), Gene expression and cancer classification (4 papers), Algorithms and Data Compression (4 papers), Data Management and Algorithms (4 papers) and Logic, Reasoning, and Knowledge (4 papers). The work is most often cited by research in Artificial Intelligence (663 citations), Information Systems (231 citations), Computer Vision and Pattern Recognition (177 citations), Computational Theory and Mathematics (116 citations) and Molecular Biology (329 citations). Jan Struyf has collaborated with scholars based in Belgium, Slovenia and Portugal. Frequent co-authors include Sašo Džeroski, Celine Vens, Hendrik Blockeel, Leander Schietgat, Dragi Kocev, David Page, Seth Dobrin, Jan Ramon, Wannes Meert and Maurice Bruynooghe. Their work appears in journals such as Machine Learning, Applied Physics Letters, Molecular BioSystems, Pattern Recognition and Ecological Modelling.

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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