Frederic Stahl

1.2k total citations
46 papers, 534 citations indexed

About

Frederic Stahl is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Frederic Stahl has authored 46 papers receiving a total of 534 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 16 papers in Information Systems and 10 papers in Computer Networks and Communications. Recurrent topics in Frederic Stahl's work include Data Stream Mining Techniques (18 papers), Machine Learning and Data Classification (10 papers) and Anomaly Detection Techniques and Applications (9 papers). Frederic Stahl is often cited by papers focused on Data Stream Mining Techniques (18 papers), Machine Learning and Data Classification (10 papers) and Anomaly Detection Techniques and Applications (9 papers). Frederic Stahl collaborates with scholars based in United Kingdom, Germany and Portugal. Frederic Stahl's co-authors include João Bártolo Gomes, Mohamed Medhat Gaber, Max Bramer, Atta Badii, Mark Tennant, Omer Rana, Oliver Zielinski, Shungudzemwoyo P. Garaba, K. Sattler and Ivan Jordanov and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Environmental Research Letters.

In The Last Decade

Frederic Stahl

44 papers receiving 508 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frederic Stahl United Kingdom 12 304 131 97 79 62 46 534
Elena Gaudioso Spain 13 159 0.5× 191 1.5× 33 0.3× 12 0.2× 36 0.6× 34 513
Da Zhu China 5 125 0.4× 136 1.0× 220 2.3× 27 0.3× 5 0.1× 8 478
Katti Faceli Brazil 10 153 0.5× 33 0.3× 15 0.2× 20 0.3× 25 0.4× 20 437
Imran Memon Pakistan 15 172 0.6× 159 1.2× 261 2.7× 51 0.6× 23 0.4× 37 629
Nguyen Khoi Tran Australia 10 156 0.5× 354 2.7× 192 2.0× 55 0.7× 8 0.1× 36 599
Tahir Riaz Denmark 8 126 0.4× 45 0.3× 142 1.5× 31 0.4× 5 0.1× 18 393
Yanxin Shi China 9 269 0.9× 243 1.9× 69 0.7× 28 0.4× 5 0.1× 25 660
Marco Gavanelli Italy 13 342 1.1× 117 0.9× 121 1.2× 35 0.4× 5 0.1× 79 546
Siddhartha Shakya United Kingdom 14 302 1.0× 22 0.2× 32 0.3× 27 0.3× 16 0.3× 59 518

Countries citing papers authored by Frederic Stahl

Since Specialization
Citations

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

Fields of papers citing papers by Frederic Stahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frederic Stahl

This figure shows the co-authorship network connecting the top 25 collaborators of Frederic Stahl. A scholar is included among the top collaborators of Frederic Stahl 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 Frederic Stahl. Frederic Stahl 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.
Zielinski, Oliver, et al.. (2024). A benchmark and survey of fully unsupervised concept drift detectors on real-world data streams. International Journal of Data Science and Analytics. 19(1). 1–31. 2 indexed citations
2.
El-Mihoub, Tarek A., et al.. (2024). On Object Detection and Explainability with Sonar Imagery. 779–786.
3.
Bramer, Max & Frederic Stahl. (2023). Artificial Intelligence XL. Lecture notes in computer science. 1 indexed citations
4.
Badii, Atta, et al.. (2023). Data-Mining and Hashing to Prevent Application-Layer DDoS and SQL Injection Attacks. CentAUR (University of Reading). 1–6. 1 indexed citations
5.
Badii, Atta, et al.. (2022). A Novel Approach Exploiting Machine Learning to Detect SQLi Attacks. CentAUR (University of Reading). 513–517. 7 indexed citations
6.
7.
Kunkel, Julian, et al.. (2022). Road Intersection Coordination Scheme for Mixed Traffic (Human Driven and Driver-Less Vehicles): A Systematic Review. Lecture notes in networks and systems. 67–94. 2 indexed citations
8.
Stahl, Frederic, et al.. (2021). A Frequent Pattern Conjunction Heuristic for Rule Generation in Data Streams. Information. 12(1). 24–24. 2 indexed citations
9.
Stahl, Frederic, et al.. (2021). ReG-Rules: An Explainable Rule-Based Ensemble Learner for Classification. IEEE Access. 9. 52015–52035. 9 indexed citations
10.
Tennant, Mark, Frederic Stahl, Omer Rana, & João Bártolo Gomes. (2017). Scalable real-time classification of data streams with concept drift. Future Generation Computer Systems. 75. 187–199. 50 indexed citations
11.
Gaber, Mohamed Medhat, et al.. (2016). A rule dynamics approach to event detection in Twitter with its application to sports and politics. Expert Systems with Applications. 55. 351–360. 57 indexed citations
12.
Fatta, Giuseppe Di, Giancarlo Fortino, Wenfeng Li, et al.. (2015). Internet and distributed computing systems - 8th international conference, IDCS 2015, Windsor, UK, September 2-4, 2015. Proceedings. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations
13.
Žliobaitė, Indrė, Marcin Budka, & Frederic Stahl. (2014). Towards cost-sensitive adaptation: When is it worth updating your predictive model?. Neurocomputing. 150. 240–249. 26 indexed citations
14.
Liu, Han, Alexander Gegov, & Frederic Stahl. (2013). J-measure based hybrid pruning for complexity reduction in classification rules. CentAUR (University of Reading). 12(9). 443–446. 7 indexed citations
15.
Stahl, Frederic, et al.. (2013). An overview of interactive visual data mining techniques for knowledge discovery. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 3(4). 239–256. 9 indexed citations
16.
Gaber, Mohamed Medhat, et al.. (2013). Pocket Data Mining: Big Data on Small Devices. CentAUR (University of Reading). 4 indexed citations
17.
Stahl, Frederic & Max Bramer. (2012). Scaling up classification rule induction through parallel processing. The Knowledge Engineering Review. 28(4). 451–478. 6 indexed citations
18.
Stahl, Frederic & Max Bramer. (2011). Jmax-pruning: A facility for the information theoretic pruning of modular classification rules. Knowledge-Based Systems. 29. 12–19. 10 indexed citations
19.
Stahl, Frederic, Mohamed Medhat Gaber, Max Bramer, & Philip S. Yu. (2010). Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments. CentAUR (University of Reading). 25. 323–330. 16 indexed citations
20.
Berrar, Daniel, et al.. (2005). Towards Data Warehousing and Mining of Protein Unfolding Simulation Data. Journal of Clinical Monitoring and Computing. 19(4-5). 307–317. 12 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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