Seppo Puuronen

1.5k total citations
51 papers, 755 citations indexed

About

Seppo Puuronen is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Seppo Puuronen has authored 51 papers receiving a total of 755 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 18 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Seppo Puuronen's work include Data Mining Algorithms and Applications (14 papers), Machine Learning and Data Classification (13 papers) and Fuzzy Logic and Control Systems (7 papers). Seppo Puuronen is often cited by papers focused on Data Mining Algorithms and Applications (14 papers), Machine Learning and Data Classification (13 papers) and Fuzzy Logic and Control Systems (7 papers). Seppo Puuronen collaborates with scholars based in Finland, Ireland and Netherlands. Seppo Puuronen's co-authors include Alexey Tsymbal, Mykola Pechenizkiy, Pádraig Cunningham, David Patterson, Ekaterina Vasilyeva, Vagan Terziyan, Elena Zaitseva, Pekka Räsänen, Vitaly Levashenko and Oleksiy Mazhelis and has published in prestigious journals such as Information Fusion, International Journal of Medical Informatics and Computers & Security.

In The Last Decade

Seppo Puuronen

48 papers receiving 687 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seppo Puuronen Finland	14	472	156	123	100	64	51	755
Michael Brückner Thailand	9	549 1.2×	128 0.8×	119 1.0×	127 1.3×	122 1.9×	24	843
William M. Pottenger United States	15	456 1.0×	200 1.3×	144 1.2×	90 0.9×	91 1.4×	57	717
Carlo Tasso Italy	16	542 1.1×	306 2.0×	86 0.7×	45 0.5×	68 1.1×	74	846
Max Bramer United Kingdom	12	354 0.8×	192 1.2×	48 0.4×	48 0.5×	64 1.0×	69	668
Angelo Gaeta Italy	14	351 0.7×	177 1.1×	100 0.8×	58 0.6×	52 0.8×	52	740
Aly A. Fahmy Egypt	9	469 1.0×	202 1.3×	60 0.5×	66 0.7×	48 0.8×	24	740
Earl Hunt	4	648 1.4×	176 1.1×	59 0.5×	73 0.7×	71 1.1×	13	924
Rajshekhar Sunderraman United States	12	213 0.5×	154 1.0×	81 0.7×	116 1.2×	214 3.3×	96	527
Panagiotis Papapetrou Sweden	17	594 1.3×	225 1.4×	161 1.3×	514 5.1×	110 1.7×	94	1.3k
Ming-Che Lee Taiwan	15	338 0.7×	247 1.6×	64 0.5×	58 0.6×	44 0.7×	53	709

Countries citing papers authored by Seppo Puuronen

Since Specialization

Citations

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

Fields of papers citing papers by Seppo Puuronen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seppo Puuronen

This figure shows the co-authorship network connecting the top 25 collaborators of Seppo Puuronen. A scholar is included among the top collaborators of Seppo Puuronen 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 Seppo Puuronen. Seppo Puuronen 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

Puuronen, Seppo & Mykola Pechenizkiy. (2010). Towards the generic framework for utility considerations in data mining research. TU/e Research Portal (Eindhoven University of Technology). 218. 3 indexed citations

Levashenko, Vitaly, Elena Zaitseva, & Seppo Puuronen. (2007). Fuzzy Classifier Based on Fuzzy Decision Tree. 823–827. 23 indexed citations

Pechenizkiy, Mykola, Alexey Tsymbal, Seppo Puuronen, & David Patterson. (2007). Feature Extraction for Dynamic Integration of Classifiers. Fundamenta Informaticae. 77(3). 243–275. 3 indexed citations

Gavrilova, Tatiana & Seppo Puuronen. (2007). COGNITIVE BIAS IN KNOWLEDGE ENGINEERING COURSE. Bulgarian Digital Mathematics Library (BulDML) at IMI-BAS (Institute of Mathematics and Informatics). 1 indexed citations

Pechenizkiy, Mykola, et al.. (2006). Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction. TU/e Research Portal. 708–713. 68 indexed citations

Pechenizkiy, Mykola, Alexey Tsymbal, & Seppo Puuronen. (2006). On combining principal components with Fisher's linear discriminants for supervised learning. Foundations of Computing and Decision Sciences. 31(1). 59–73. 6 indexed citations

Pechenizkiy, Mykola, Alexey Tsymbal, & Seppo Puuronen. (2006). Local Dimensionality Reduction and Supervised Learning Within Natural Clusters for Biomedical Data Analysis. IEEE Transactions on Information Technology in Biomedicine. 10(3). 533–539. 7 indexed citations

Puuronen, Seppo, Mykola Pechenizkiy, & Alexey Tsymbal. (2006). Data Mining Researcher, Who is Your Customer? Some Issues Inspired by the Information Systems Field. Data Archiving and Networked Services (DANS). 579–583. 1 indexed citations

Vasilyeva, Ekaterina, Mykola Pechenizkiy, & Seppo Puuronen. (2005). Towards the Framework of Adaptive User Interfaces for eHealth. TU/e Research Portal. 139–144. 26 indexed citations

10.

Zaitseva, Elena, et al.. (2005). Dynamic Reliability Indices for k-out-of-n Multi-State System. 61. 264–269. 4 indexed citations

11.

Tsymbal, Alexey, Seppo Puuronen, & David Patterson. (2003). Ensemble feature selection with the simple Bayesian classification. Information Fusion. 4(2). 87–100. 117 indexed citations

12.

Pechenizkiy, Mykola, Seppo Puuronen, & Alexey Tsymbal. (2003). Feature extraction for classification in the data mining process. Bulgarian Digital Mathematics Library (BulDML) at IMI-BAS (Institute of Mathematics and Informatics). 10(1). 271–278. 4 indexed citations

13.

Tsymbal, Alexey, Seppo Puuronen, Mykola Pechenizkiy, Matthias Baumgarten, & David Patterson. (2002). Eigenvector-Based Feature Extraction for Classification. Data Archiving and Networked Services (DANS). 354–358. 24 indexed citations

14.

Puuronen, Seppo, et al.. (2002). HIDSUR: a hybrid intrusion detection system based on real-time user recognition. 41–45. 5 indexed citations

15.

Tsymbal, Alexey, et al.. (2000). Local feature selection for heterogeneous problems. 25. 203–212. 1 indexed citations

16.

Puuronen, Seppo, et al.. (1999). Anomaly Intrusion Detection Systems: Handling Temporal Relations Between Events.. 15 indexed citations

17.

Ryabov, V. B., Seppo Puuronen, & Vagan Terziyan. (1999). Representation and Reasoning with Uncertain Temporal Relations. The Florida AI Research Society. 449–453. 5 indexed citations

18.

Puuronen, Seppo, et al.. (1999). <title>Dynamic integration of multiple data mining techniques in a knowledge discovery management system</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3695. 128–139. 6 indexed citations

19.

Terziyan, Vagan, Alexey Tsymbal, & Seppo Puuronen. (1998). The decision support system for telemedicine based on multiple expertise. International Journal of Medical Informatics. 49(2). 217–229. 11 indexed citations

20.

Puuronen, Seppo, et al.. (1997). Mobile information systems — executives' view. Information Systems Journal. 7(1). 3–20. 10 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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