Peter Geibel

544 total citations
20 papers, 146 citations indexed

About

Peter Geibel is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Peter Geibel has authored 20 papers receiving a total of 146 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Information Systems. Recurrent topics in Peter Geibel's work include Semantic Web and Ontologies (6 papers), Imbalanced Data Classification Techniques (4 papers) and Text and Document Classification Technologies (4 papers). Peter Geibel is often cited by papers focused on Semantic Web and Ontologies (6 papers), Imbalanced Data Classification Techniques (4 papers) and Text and Document Classification Technologies (4 papers). Peter Geibel collaborates with scholars based in Germany, United States and France. Peter Geibel's co-authors include Fritz Wysotzki, Konstantin Todorov, Alexander Mehler, Ulf Brefeld, Adrian Popescu, Brijnesh J. Jain, Céline Hudelot, Christian H. Nolte, Thomas Tolxdorff and Hebun Erdur and has published in prestigious journals such as Neurocomputing, Applied Intelligence and International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.

In The Last Decade

Peter Geibel

20 papers receiving 127 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peter Geibel Germany	8	119	33	23	18	16	20	146
Ingo Thon Belgium	7	141 1.2×	13 0.4×	16 0.7×	17 0.9×	20 1.3×	15	162
David Evans United Kingdom	6	133 1.1×	41 1.2×	18 0.8×	12 0.7×	31 1.9×	25	199
Sang-Hyeun Park Germany	6	138 1.2×	34 1.0×	30 1.3×	12 0.7×	4 0.3×	7	156
Jiawei Han China	5	105 0.9×	41 1.2×	57 2.5×	24 1.3×	15 0.9×	9	168
Ming Tan United States	6	216 1.8×	69 2.1×	32 1.4×	32 1.8×	20 1.3×	13	241
Elena Botoeva United Kingdom	8	135 1.1×	27 0.8×	18 0.8×	10 0.6×	68 4.3×	21	157
Marenglen Biba Italy	6	66 0.6×	24 0.7×	19 0.8×	10 0.6×	43 2.7×	27	130
Siyuan Cheng China	6	117 1.0×	10 0.3×	32 1.4×	17 0.9×	10 0.6×	15	144
Patrick K. Nicholson United States	7	73 0.6×	41 1.2×	13 0.6×	5 0.3×	68 4.3×	22	158
Jieun Eom South Korea	4	201 1.7×	65 2.0×	48 2.1×	19 1.1×	27 1.7×	5	235

Countries citing papers authored by Peter Geibel

Since Specialization

Citations

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

Fields of papers citing papers by Peter Geibel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Geibel

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

Blobel, Bernd, et al.. (2016). How to Work with Vocabulary Correctly, Exemplified with Gender Coding?. Studies in health technology and informatics. 228. 344–8. 1 indexed citations

Todorov, Konstantin, Céline Hudelot, Adrian Popescu, & Peter Geibel. (2014). FUZZY ONTOLOGY ALIGNMENT USING BACKGROUND KNOWLEDGE. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 22(1). 75–112. 11 indexed citations

Geibel, Peter, et al.. (2014). Ontology-Based Information Extraction: Identifying Eligible Patients for Clinical Trials in Neurology. 4(2). 133–147. 11 indexed citations

Todorov, Konstantin & Peter Geibel. (2009). Variable Selection as an Instance-Based Ontology Mapping Strategy.. 3–9. 3 indexed citations

Wysotzki, Fritz & Peter Geibel. (2009). A New Information Measure Based on Example-Dependent Misclassification Costs and Its Application in Decision Tree Learning. Hindawi Journal of Chemistry (Hindawi). 2009. 1–13. 2 indexed citations

Todorov, Konstantin & Peter Geibel. (2008). Ontology mapping via structural and instance-based similarity measures. 224–228. 6 indexed citations

Kühnberger, Kai‐Uwe, et al.. (2008). Learning from Inconsistencies in an Integrated Cognitive Architecture. 37(9). 212–223. 2 indexed citations

Mehler, Alexander, et al.. (2007). Structural classiﬁers of text types: Towards a novel model of text representation. PUB – Publications at Bielefeld University (Bielefeld University). 22(2). 66–4. 12 indexed citations

Mehler, Alexander, et al.. (2007). Structural Classifiers of Text Types: Towards a Novel Model of Text Representation. 22(2). 51–66. 7 indexed citations

10.

Kühnberger, Kai‐Uwe, et al.. (2007). Modeling Human-Level Intelligence by Integrated Cognition in a Hybrid Architecture.. 1 indexed citations

11.

Geibel, Peter. (2007). Reinforcement Learning Approaches for Constrained MDPs. 3(1). 3 indexed citations

12.

Jain, Brijnesh J., Peter Geibel, & Fritz Wysotzki. (2005). SVM learning with the Schur–Hadamard inner product for graphs. Neurocomputing. 64. 93–105. 9 indexed citations

13.

Geibel, Peter, Brijnesh J. Jain, & Fritz Wysotzki. (2004). SVM learning with the SH inner product.. The European Symposium on Artificial Neural Networks. 299–304. 1 indexed citations

14.

Geibel, Peter & Fritz Wysotzki. (2004). Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs. Applied Intelligence. 21(1). 45–56. 6 indexed citations

15.

Geibel, Peter, Ulf Brefeld, & Fritz Wysotzki. (2004). Perceptron and SVM learning with generalized cost models. Intelligent Data Analysis. 8(5). 439–455. 13 indexed citations

16.

Geibel, Peter & Fritz Wysotzki. (2003). Perceptron based learning with example dependent and noisy costs. International Conference on Machine Learning. 218–225. 11 indexed citations

17.

Geibel, Peter, et al.. (2003). Connectionist construction of prototypes from decision trees for graph classification. Intelligent Data Analysis. 7(2). 125–140. 2 indexed citations

18.

Geibel, Peter. (2001). Reinforcement Learning with Bounded Risk. International Conference on Machine Learning. 162–169. 26 indexed citations

19.

Geibel, Peter & Fritz Wysotzki. (1996). Relational Learning with Decision Trees.. European Conference on Artificial Intelligence. 428–432. 4 indexed citations

20.

Geibel, Peter & Fritz Wysotzki. (1996). Learning Relational Concepts with Decision Trees.. International Conference on Machine Learning. 166–174. 15 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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