Christine Preisach

467 citations
5 papers · 298 indexed · h-index 4
Topics
Text and Document Classification Technologies (2 papers)Advanced Graph Neural Networks (2 papers)Bayesian Modeling and Causal Inference (2 papers)
Journals
Knowledge and Information SystemsCERN Document Server (European Organization for Nuclear Research)Springer eBooks
Partner nations
Germany

In The Last Decade

Christine Preisach

5 papers receiving 282 citations

Peers

Christine Preisach
Comparison fields: 5 of 117
  • Artificial Intelligence 83
  • Molecular Biology 77
  • Computational Theory and Mathematics 56
  • Information Systems 40
  • Signal Processing 34
Replace Yasumasa Baba with:
Yasumasa Baba Japan
J. Gerard Wolff United Kingdom
Simon Clematide Switzerland
Mateja Jamnik United Kingdom
Kimmo Kettunen Finland
Gregor Leban Slovenia
Emanuele Pianta Italy
Fiona Browne United Kingdom
Steffen Schulze-Kremer Germany
David Milward United Kingdom
Christine Preisach relative to Yasumasa Baba Japan Yasumasa Baba's profile →
Citations per field
00.5×3.2×
Yasumasa Baba · 1×
Citations per year

Countries citing papers authored by Christine Preisach

Since Specialization
Citations

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

Fields of papers citing papers by Christine Preisach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christine Preisach

This figure shows the co-authorship network connecting the top 25 collaborators of Christine Preisach. A scholar is included among the top collaborators of Christine Preisach 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 Christine Preisach. Christine Preisach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1
Relational classification for personalized tag recommendation
11
2
Data Analysis, Machine Learning and Applications: Proceedings of the 31st Annual Conference of the Gesellschaft fr Klassifikation e.V., Albert-Ludwigs-Universitt ... Data Analysis, and Knowledge Organization)
2
3 253
4 20
5 12

About Christine Preisach

Christine Preisach is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 5 papers that have together received 298 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (2 papers), Advanced Graph Neural Networks (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Computational Theory and Mathematics (56 citations), Computational Mathematics (2 citations) and Signal Processing (34 citations). Christine Preisach has collaborated with scholars based in Germany. Frequent co-authors include Lars Schmidt-Thieme, Leandro Balby Marinho, Hans Burkhardt and Reinhold Decker. Their work appears in journals such as Knowledge and Information Systems, CERN Document Server (European Organization for Nuclear Research) and Springer eBooks.

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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