Seppo Puuronen

1.5k citations
51 papers · 755 indexed · h-index 14
Topics
Data Mining Algorithms and Applications (14 papers)Machine Learning and Data Classification (13 papers)Fuzzy Logic and Control Systems (7 papers)

In The Last Decade

Seppo Puuronen

48 papers receiving 687 citations

Peers

Seppo Puuronen
Comparison fields: 5 of 115
  • Artificial Intelligence 472
  • Information Systems 156
  • Computer Vision and Pattern Recognition 123
  • Signal Processing 100
  • Computer Networks and Communications 64
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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

20 of 20 papers shown
#WorkIndexed citations
1
Towards the generic framework for utility considerations in data mining research
3
2 23
3 3
4
COGNITIVE BIAS IN KNOWLEDGE ENGINEERING COURSE
1
5 68
6
On combining principal components with Fisher's linear discriminants for supervised learning
6
7 7
8
Data Mining Researcher, Who is Your Customer? Some Issues Inspired by the Information Systems Field
1
9 26
10 4
11 117
12
Feature extraction for classification in the data mining process
4
13
Eigenvector-Based Feature Extraction for Classification
24
14 5
15 1
16
Anomaly Intrusion Detection Systems: Handling Temporal Relations Between Events.
15
17
Representation and Reasoning with Uncertain Temporal Relations
5
18 6
19 11
20 10

About Seppo Puuronen

Seppo Puuronen is a scholar working on Artificial Intelligence, Information Systems and Management Information Systems, having authored 51 papers that have together received 755 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (14 papers), Machine Learning and Data Classification (13 papers) and Fuzzy Logic and Control Systems (7 papers). The work is most often cited by research in Artificial Intelligence (472 citations), Signal Processing (100 citations) and Information Systems (156 citations). Seppo Puuronen has collaborated with scholars based in Finland, Ireland and Netherlands. Frequent co-authors include Alexey Tsymbal, Mykola Pechenizkiy, Pádraig Cunningham, David Patterson, Ekaterina Vasilyeva, Vagan Terziyan, Elena Zaitseva, Pekka Räsänen, Vitaly Levashenko and Oleksiy Mazhelis. Their work appears in journals such as Information Fusion, International Journal of Medical Informatics and Computers & Security.

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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