Štefan Dlugolinský

1.2k total citations · 1 hit paper
25 papers, 650 citations indexed

About

Štefan Dlugolinský is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Štefan Dlugolinský has authored 25 papers receiving a total of 650 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 13 papers in Information Systems and 5 papers in Computer Networks and Communications. Recurrent topics in Štefan Dlugolinský's work include Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers) and Personal Information Management and User Behavior (4 papers). Štefan Dlugolinský is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers) and Personal Information Management and User Behavior (4 papers). Štefan Dlugolinský collaborates with scholars based in Slovakia, Poland and Spain. Štefan Dlugolinský's co-authors include Giang Nguyen, Viet Tran, Álvaro López García, Ladislav Hluchý, Peter Malík, Ignacio Heredia, Martin Bobák, Michal Laclavík, Jacek Kitowski and Peter H. Krammer and has published in prestigious journals such as IEEE Access, Neural Computing and Applications and Artificial Intelligence Review.

In The Last Decade

Štefan Dlugolinský

25 papers receiving 610 citations

Hit Papers

Machine Learning and Deep Learning frameworks and librari... 2019 2026 2021 2023 2019 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey
    2019 516 citations Giang Nguyen, Štefan Dlugolinský et al. Artificial Intelligence Review profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Štefan Dlugolinský Slovakia 6 245 128 111 73 62 25 650
Viet Tran Slovakia 10 249 1.0× 185 1.4× 123 1.1× 83 1.1× 70 1.1× 65 982
Martin Bobák Slovakia 5 179 0.7× 86 0.7× 78 0.7× 72 1.0× 40 0.6× 21 555
Bin Qian China 7 327 1.3× 121 0.9× 80 0.7× 95 1.3× 34 0.5× 15 725
Peter Malík Slovakia 7 195 0.8× 80 0.6× 72 0.6× 92 1.3× 69 1.1× 31 625
Ramzan Talib Pakistan 8 286 1.2× 77 0.6× 141 1.3× 116 1.6× 44 0.7× 26 667
Subrota Kumar Mondal Macao 10 258 1.1× 124 1.0× 188 1.7× 117 1.6× 46 0.7× 34 664
Ignacio Heredia Spain 4 175 0.7× 74 0.6× 68 0.6× 69 0.9× 40 0.6× 15 545
Soumi Ghosh India 9 178 0.7× 92 0.7× 177 1.6× 102 1.4× 53 0.9× 30 578
Antti Evesti Finland 12 194 0.8× 169 1.3× 258 2.3× 110 1.5× 75 1.2× 31 723
Dave Braines United Kingdom 14 503 2.1× 110 0.9× 117 1.1× 72 1.0× 33 0.5× 75 899

Countries citing papers authored by Štefan Dlugolinský

Since Specialization
Citations

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

Fields of papers citing papers by Štefan Dlugolinský

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Štefan Dlugolinský

This figure shows the co-authorship network connecting the top 25 collaborators of Štefan Dlugolinský. A scholar is included among the top collaborators of Štefan Dlugolinský 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 Štefan Dlugolinský. Štefan Dlugolinský 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
1.
Nguyen, Giang, Štefan Dlugolinský, Viet Tran, & Álvaro López García. (2024). Network security AIOps for online stream data monitoring. Neural Computing and Applications. 36(24). 14925–14949. 4 indexed citations
2.
Staňo, Michal, et al.. (2023). Classification of Tree Species by Federated Learning. 60. 1–6. 2 indexed citations
3.
Nguyen, Giang, et al.. (2021). A comparative study of operational engineering for environmental and compute-intensive applications. Array. 12. 100096–100096. 4 indexed citations
4.
Nguyen, Giang, Štefan Dlugolinský, Viet Tran, & Álvaro López García. (2020). Deep Learning for Proactive Network Monitoring and Security Protection. IEEE Access. 8. 19696–19716. 51 indexed citations
5.
Nguyen, Giang, Štefan Dlugolinský, Martin Bobák, et al.. (2019). Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey. Artificial Intelligence Review. 52(1). 77–124. 516 indexed citations breakdown →
6.
Laclavík, Michal, et al.. (2015). Discovering Relations by Entity Search in Lightweight Semantic Text Graphs. Computing and Informatics / Computers and Artificial Intelligence. 33(4). 877–906. 2 indexed citations
7.
Hluchý, Ladislav, Štefan Dlugolinský, Bernhard Schneider, et al.. (2015). A Novel Way of Using Simulations to Support Urban Security Operations. Computing and Informatics / Computers and Artificial Intelligence. 34(6). 1201–1233. 3 indexed citations
8.
Laclavík, Michal, et al.. (2015). Search Query Categorization at Scale. 1281–1286. 4 indexed citations
9.
Dlugolinský, Štefan, et al.. (2014). Combining Named Entity Recognition Methods for Concept Extraction in Microposts.. 34–41. 2 indexed citations
10.
Laclavík, Michal, et al.. (2014). A search based approach to entity recognition. 63–68. 4 indexed citations
11.
Laclavík, Michal, et al.. (2014). Approach for enterprise search and interoperability using lightweight semantic. 30. 73–78. 1 indexed citations
12.
Dlugolinský, Štefan, et al.. (2013). MSM2013 IE Challenge: Annotowatch. 21–26. 3 indexed citations
13.
Dlugolinský, Štefan, et al.. (2013). Character gazetteer for Named Entity Recognition with linear matching complexity. 4013. 361–365. 3 indexed citations
14.
Hluchý, Ladislav, Štefan Dlugolinský, Michal Laclavík, et al.. (2012). An integrated approach to mission analysis and mission rehearsal. 362. 2 indexed citations
15.
Laclavík, Michal, et al.. (2012). Emails as graph. Zenodo (CERN European Organization for Nuclear Research). 841–846. 11 indexed citations
16.
Laclavík, Michal, et al.. (2012). Lightweight Semantic Approach for Enterprise Search and Interoperability.. 35–42. 2 indexed citations
17.
Hluchý, Ladislav, et al.. (2011). Handling internal complexity in highly realistic agent-based models of human behaviour. 25. 11–16. 5 indexed citations
18.
Laclavík, Michal, et al.. (2011). Email Social Network Extraction and Search. 30. 373–376. 4 indexed citations
19.
Laclavík, Michal, et al.. (2010). Reconstructing Social Networks from Emails. 50–59. 4 indexed citations
20.
Dlugolinský, Štefan, Michal Laclavík, & Ladislav Hluchý. (2010). Towards a Search System for the Web Exploiting Spatial Data of a Web Document. 28. 27–31. 2 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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