Ralf Klinkenberg

2.5k citations
32 papers · 2.0k · 1 hit paper · h-index 15

Impact in

    • Data Stream Mining Techniques
    • Machine Learning and Data Classification
    • Anomaly Detection Techniques and Applications
    • Imbalanced Data Classification Techniques
    • Text and Document Classification Technologies
    • Time Series Analysis and Forecasting

Papers in

Ralf Klinkenberg

29 papers receiving 1.8k citations

Ralf Klinkenberg's Hit Papers

YALE 2006 · 826 citations
8260+6+13Years since publication250500750

Peers

Ralf Klinkenberg
Comparison fields: 5 of 131
  • Artificial Intelligence 1.4k
  • Signal Processing 315
  • Information Systems 416
  • Management Science and Operations Research 219
  • Computer Science Applications 91
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Citations per year

Countries citing papers authored by Ralf Klinkenberg

Since Specialization
Citations

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

Fields of papers citing papers by Ralf Klinkenberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ralf Klinkenberg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ralf Klinkenberg Line = papers co-authored together Ralf Klinkenberg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
YALE
Hit paper breakdown →
2006826
2 2004328
3
Detecting Concept Drift with Support Vector Machines
2000316
4
Adaptive Information Filtering: Learning in the Presence of Concept Drifts
1998113
5 200687
6 200764
7 200235
8 200235
9
Using Labeled and Unlabeled Data to Learn Drifting Concepts
200126
10
Concept Drift and the Importance of Example.
200326
11
Meta-Learning, Model Selection, and Example Selection in Machine Learning Domains with Concept Drift.
200522
12 201417
13 200817
14 202115
15 201614
16
A Flexible Platform for Knowledge Discovery Experiments: YALE - Yet Another Learning Environment
200310
17 202010
18 20207
19 20216
20
Predicting Phases in Business Cycles Under Concept Drift
20035

About Ralf Klinkenberg

Ralf Klinkenberg is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Industrial and Manufacturing Engineering and Computer Networks and Communications, having authored 32 papers that have together received 2.0k indexed citations. Recurring topics across this work include Data Stream Mining Techniques (12 papers), Machine Learning and Data Classification (6 papers), Flexible and Reconfigurable Manufacturing Systems (4 papers), Advanced Bandit Algorithms Research (4 papers), Data Quality and Management (3 papers), Advanced Database Systems and Queries (2 papers), Manufacturing Process and Optimization (2 papers) and Aging, Elder Care, and Social Issues (2 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Signal Processing (315 citations), Information Systems (416 citations), Management Science and Operations Research (219 citations) and Computer Science Applications (91 citations). Ralf Klinkenberg has collaborated with scholars based in Germany, Greece and Spain. Frequent co-authors include Martin Scholz, Ingo Mierswa, Michael Wurst, Thorsten Joachims, Stefan Rüping, Simon Fischer, Jochen Deuse, Jesús S. Aguilar–Ruiz, João Gama and Alexandros–Apostolos A. Boulogeorgos. Their work appears in journals such as IEEE Technology and Society Magazine, Intelligent Data Analysis, Lecture notes in computer science, Natural computing series and LWA.

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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