Filip Železný

1.4k citations
48 papers · 584 indexed · h-index 14
Topics
Data Mining Algorithms and Applications (9 papers)Gene expression and cancer classification (9 papers)Semantic Web and Ontologies (7 papers)

In The Last Decade

Filip Železný

44 papers receiving 553 citations

Peers

Filip Železný
Comparison fields: 5 of 108
  • Artificial Intelligence 272
  • Information Systems 159
  • Molecular Biology 125
  • Computational Theory and Mathematics 88
  • Economics and Econometrics 74
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Countries citing papers authored by Filip Železný

Since Specialization
Citations

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

Fields of papers citing papers by Filip Železný

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Filip Železný

This figure shows the co-authorship network connecting the top 25 collaborators of Filip Železný. A scholar is included among the top collaborators of Filip Železný 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 Filip Železný. Filip Železný 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 0
2 3
3 39
4 3
5
Lifted relational neural networks
2
6 9
7 12
8
Machine learning and knowledge discovery in databases, European Conference, ECML PKDD 2013, Proceedings, Part III
4
9 19
10 6
11 14
12 10
13
A Performance Prediction Module for Workflow Scheduling
2
14
A comparative evaluation of gene set analysis techniques in predictive classification of expression samples
3
15
Formulating template consistency in inductive logic programming as a constraint satisfaction problem
0
16
Cross-genome knowledge-based expression data fusion
2
17
A Restarted Strategy for Efficient Subsumption Testing
5
18 2
19
Relational Descriptive Analysis of Gene Expression Data
1
20 32

About Filip Železný

Filip Železný is a scholar working on Artificial Intelligence, Transplantation and Computational Theory and Mathematics, having authored 48 papers that have together received 584 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (9 papers), Gene expression and cancer classification (9 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Artificial Intelligence (272 citations), Transplantation (20 citations) and Information Systems (159 citations). Filip Železný has collaborated with scholars based in Czechia, United States and Slovenia. Frequent co-authors include Nada Lavrač, Ondřej Kuželka, Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Jakub Tolar, Jǐŕı Kléma, Steven Schockaert, Dragan Gamberger and C. David Page. Their work appears in journals such as BMC Bioinformatics, Transplantation and BMC Genomics.

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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