Artur Bykowski

654 total citations
3 papers, 187 citations indexed

About

Artur Bykowski is a scholar working on Information Systems, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Artur Bykowski has authored 3 papers receiving a total of 187 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Information Systems, 3 papers in Computational Theory and Mathematics and 1 paper in Computer Networks and Communications. Recurrent topics in Artur Bykowski's work include Rough Sets and Fuzzy Logic (3 papers), Data Mining Algorithms and Applications (3 papers) and Imbalanced Data Classification Techniques (1 paper). Artur Bykowski is often cited by papers focused on Rough Sets and Fuzzy Logic (3 papers), Data Mining Algorithms and Applications (3 papers) and Imbalanced Data Classification Techniques (1 paper). Artur Bykowski collaborates with scholars based in France. Artur Bykowski's co-authors include Christophe Rigotti and Jean‐François Boulicaut and has published in prestigious journals such as Data Mining and Knowledge Discovery and Information Systems.

In The Last Decade

Artur Bykowski

3 papers receiving 169 citations

Peers

Artur Bykowski

IS

CTM

SP

AI

CNC

P. Palmerini Italy

Souleymane Zida Canada

Jeremy W. Nimmer United States

Shan-Hwei Nienhuys-Cheng Netherlands

Aaron Tomb United States

Ru-Gang Xu United States

Yasuhiko Minamide Japan

Hyoung Seok Hong South Korea

Gilberto Filé Italy

Jacob Matthews United States

P. Palmerini Italy

Artur Bykowski

143 ×0.8

IS

87 ×0.6

CTM

65 ×0.8

SP

61 ×0.8

AI

36 ×1.6

CNC

Citations per year, relative to Artur Bykowski Artur Bykowski (= 1×) peers P. Palmerini

Countries citing papers authored by Artur Bykowski

Since Specialization

Citations

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

Fields of papers citing papers by Artur Bykowski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Artur Bykowski

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

All Works

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3 of 3 papers shown

1.

Bykowski, Artur & Christophe Rigotti. (2003). DBC: a condensed representation of frequent patterns for efficient mining. Information Systems. 28(8). 949–977. 18 indexed citations

2.

Boulicaut, Jean‐François, Artur Bykowski, & Christophe Rigotti. (2003). Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries. Data Mining and Knowledge Discovery. 7(1). 5–22. 112 indexed citations

3.

Bykowski, Artur & Christophe Rigotti. (2001). A condensed representation to find frequent patterns. 267–273. 57 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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