Jan Rauch

918 total citations
42 papers, 330 citations indexed

About

Jan Rauch is a scholar working on Information Systems, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Jan Rauch has authored 42 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Information Systems, 22 papers in Computational Theory and Mathematics and 14 papers in Artificial Intelligence. Recurrent topics in Jan Rauch's work include Rough Sets and Fuzzy Logic (22 papers), Data Mining Algorithms and Applications (22 papers) and Advanced Database Systems and Queries (10 papers). Jan Rauch is often cited by papers focused on Rough Sets and Fuzzy Logic (22 papers), Data Mining Algorithms and Applications (22 papers) and Advanced Database Systems and Queries (10 papers). Jan Rauch collaborates with scholars based in Czechia, Sweden and United States. Jan Rauch's co-authors include Milan Šimůnek, Petr Hájek, Martin Holeňa, Petr Berka, Jan M. Żytkow, Djamel A. Zighed, Vojtěch Svátek, Tapio Elomaa, Jan Peleška and Jaroslav Pokorný and has published in prestigious journals such as Knowledge-Based Systems, Journal of Computer and System Sciences and Lecture notes in computer science.

In The Last Decade

Jan Rauch

40 papers receiving 302 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jan Rauch Czechia	10	202	185	150	52	43	42	330
Alicja Wakulicz–Deja Poland	12	201 1.0×	106 0.6×	134 0.9×	35 0.7×	22 0.5×	33	345
Marcel Holsheimer Netherlands	7	144 0.7×	202 1.1×	88 0.6×	76 1.5×	53 1.2×	7	323
Tharam S. Dillon Australia	10	159 0.8×	204 1.1×	43 0.3×	52 1.0×	75 1.7×	38	307
Philip Dart Australia	9	289 1.4×	118 0.6×	88 0.6×	40 0.8×	37 0.9×	18	383
Azadeh Soltani Iran	3	156 0.8×	231 1.2×	122 0.8×	72 1.4×	53 1.2×	9	315
Antonio Gomariz Spain	3	143 0.7×	219 1.2×	117 0.8×	70 1.3×	42 1.0×	4	281
Jörg-Uwe Kietz Switzerland	8	310 1.5×	149 0.8×	58 0.4×	27 0.5×	49 1.1×	16	365
Thu-Lan Dam China	8	164 0.8×	275 1.5×	212 1.4×	97 1.9×	27 0.6×	12	316
Ted Gueniche Canada	2	156 0.8×	244 1.3×	136 0.9×	81 1.6×	43 1.0×	2	305
Fabio Fioravanti Italy	9	116 0.6×	146 0.8×	95 0.6×	40 0.8×	108 2.5×	36	284

Countries citing papers authored by Jan Rauch

Since Specialization

Citations

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

Fields of papers citing papers by Jan Rauch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Rauch

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

All Works

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20 of 20 papers shown

1.

Rauch, Jan, et al.. (2024). A novel algorithm weighting different importance of classes in enhanced association rules. Knowledge-Based Systems. 294. 111741–111741. 1 indexed citations

2.

Rauch, Jan, et al.. (2023). A novel algorithm for mining couples of enhanced association rules based on the number of output couples and its application. Journal of Intelligent Information Systems. 62(2). 431–458. 2 indexed citations

3.

Rauch, Jan & Milan Šimůnek. (2017). Apriori and GUHA – Comparing two approaches to data mining with association rules. Intelligent Data Analysis. 21(4). 981–1013. 9 indexed citations

4.

Rauch, Jan. (2015). Formal Framework for Data Mining with Association Rules and Domain Knowledge – Overview of an Approach. Fundamenta Informaticae. 137(2). 171–217. 7 indexed citations

5.

Zvárová, Jana, et al.. (2012). EuroMISE Center: research and education in biomedical and healthcare informatics.. PubMed. 174. 53–6. 3 indexed citations

6.

Rauch, Jan. (2011). Consideration on a formal frame for data mining. 562–569. 3 indexed citations

7.

Rauch, Jan. (2010). Modifying Logic of Discovery for Dealing with Domain Knowledge in Data Mining.. 175–186. 1 indexed citations

8.

Kliegr, Tomáš, et al.. (2010). SEWEBAR-CMS: A System for Postprocessing Data Mining Models.. 1 indexed citations

9.

Hájek, Petr, Martin Holeňa, & Jan Rauch. (2009). The GUHA method and its meaning for data mining. Journal of Computer and System Sciences. 76(1). 34–48. 40 indexed citations

10.

Svátek, Vojtěch & Jan Rauch. (2008). Ontology-Enhanced Association Mining. 2 indexed citations

11.

Berka, Petr, et al.. (2007). Lessons Learned from the ECML/PKDD Discovery Challenge on the Atherosclerosis Risk Factors Data.. Computing and Informatics / Computers and Artificial Intelligence. 26(3). 329–344. 3 indexed citations

12.

Rauch, Jan. (2007). Project SEWEBAR Considerations on Semantic Web and Data Mining.. Indian International Conference on Artificial Intelligence. 1763–1782. 3 indexed citations

13.

Feelders, Ad, Jan M. Żytkow, & Jan Rauch. (2007). Handling Missing Data in Trees: Surrogate Splits Or Statistical Imputation?. Research portal (Tilburg University). 5 indexed citations

14.

Rauch, Jan & Milan Šimůnek. (2007). Semantic Web Presentation of Analytical Reports from Data Mining - Preliminary Considerations. 44. 3–7. 8 indexed citations

15.

Rauch, Jan & Milan Šimůnek. (2005). An Alternative Approach to Mining Association Rules.. 211–231. 40 indexed citations

16.

Rauch, Jan. (2004). Logic of Association Rules. Applied Intelligence. 22(1). 9–28. 41 indexed citations

17.

Rauch, Jan & Milan Šimůnek. (2001). Mining for Association Rules by 4ft-Miner.. 285–295. 6 indexed citations

18.

Żytkow, Jan M. & Jan Rauch. (1999). Principles of data mining and knowledge discovery : Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999 : proceedings. Springer eBooks. 5 indexed citations

19.

Rauch, Jan. (1975). Ein Beitrag zu der GUHA Methode in der dreiwertigen Logik. Kybernetika. 11(2). 8 indexed citations

20.

Rauch, Jan. (1975). A remark to the GUHA method in the three-valued logic.. Kybernetika. 11. 101–113. 4 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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