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).
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-authorship network of co-authors of Jan Struyf
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Struyf.
A scholar is included among the top collaborators of Jan Struyf 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 Jan Struyf. Jan Struyf 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.
Meert, Wannes, Jan Struyf, & Hendrik Blockeel. (2010). Contextual variable elimination with overlapping contexts. Lirias (KU Leuven). 193–201.
Meert, Wannes, Jan Struyf, & Hendrik Blockeel. (2008). Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques. Fundamenta Informaticae. 89(1). 131–160.21 indexed citations
5.
Meert, Wannes, Jan Struyf, & Hendrik Blockeel. (2008). Learning Ground CP-logic Theories by means of Bayesian Network Techniques. Lirias (KU Leuven).5 indexed citations
Džeroski, Sašo, et al.. (2007). Knowledge discovery in inductive databases : 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006 : revised selected and invited papers. Springer eBooks.4 indexed citations
8.
Davis, Jesse, Irene M. Ong, Jan Struyf, et al.. (2007). Change of representation for statistical relational learning. International Joint Conference on Artificial Intelligence. 16(2). 2719–2726.20 indexed citations
9.
Struyf, Jan, et al.. (2007). First Order Alternating Decision Trees. Lirias (KU Leuven).1 indexed citations
10.
Schietgat, Leander, Hendrik Blockeel, Jan Struyf, Sašo Džeroski, & Amanda Clare. (2006). Decision trees for hierarchical multilabel classification: A case study in functional genomics. Lirias (KU Leuven). 423–424.13 indexed citations
11.
Struyf, Jan, Celine Vens, Tom Croonenborghs, Sašo Džeroski, & Hendrik Blockeel. (2005). Applying predictive clustering trees to the inductive logic programming 2005 challenge data. Lirias (KU Leuven). 111–116.1 indexed citations
12.
Ramon, Jan & Jan Struyf. (2004). Efficient theta-subsumption of sets of patterns. Lirias (KU Leuven). 95–102.1 indexed citations
13.
Struyf, Jan, et al.. (2003). Query optimization: Combining query packs and the once-tranformation. Lirias (KU Leuven). 105–115.2 indexed citations
14.
Verbaeten, Sofie, et al.. (2003). Attribute-value and first order data mining within the STULONG project. Lirias (KU Leuven). 108–119.
15.
Costa, Vı́tor Santos, Ashwin Srinivasan, Rui Camacho, et al.. (2003). Query transformations for improving the efficiency of ilp systems. Journal of Machine Learning Research. 4(4). 465–491.24 indexed citations
16.
Blockeel, Hendrik, Maurice Bruynooghe, Sašo Džeroski, Jan Ramon, & Jan Struyf. (2002). Hierarchical multi-classification. Lirias (KU Leuven). 21–35.46 indexed citations
17.
Blockeel, Hendrik, Kurt Driessens, Jan Ramon, et al.. (2001). First order models for the predictive toxicology challenge. Lirias (KU Leuven). 1–12.2 indexed citations
18.
Blockeel, Hendrik & Jan Struyf. (2001). Deriving biased classifiers for better ROC performance. The Information Society. 26(1). 124–127.5 indexed citations
19.
Blockeel, Hendrik & Jan Struyf. (2001). Frankenstein classifiers: Some experiments on the Sisyphus data set. Lirias (KU Leuven). 1–12.
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.