Carsten Eickhoff

4.2k citations
132 papers · 2.2k · h-index 22

Impact in

Papers in

    • Topic Modeling 35
    • Natural Language Processing Techniques 20
    • Machine Learning in Healthcare 10
    • Information Retrieval and Search Behavior 21
    • Recommender Systems and Techniques 9
    • Web Data Mining and Analysis 8

Carsten Eickhoff

118 papers receiving 2.1k citations

Peers

Carsten Eickhoff
Comparison fields: 5 of 138
  • Health Informatics 168
  • Computer Science Applications 394
  • Artificial Intelligence 835
  • Information Systems 444
  • Management Science and Operations Research 183
Replace Nazar Zaki with:
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Citations per field
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Citations per year

Countries citing papers authored by Carsten Eickhoff

Since Specialization
Citations

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

Fields of papers citing papers by Carsten Eickhoff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Carsten Eickhoff, 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 Carsten Eickhoff Line = papers co-authored together Carsten Eickhoff links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 132 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018244
2 2012158
3 2012129
4 2014111
5 2018104
6 202097
7 201691
8 202282
9 202182
10 201171
11 202061
12 202057
13
How Crowdsourcable is Your Task
201154
14 202452
15 202346
16 201840
17 201739
18 201533
19 201131
20 201823

About Carsten Eickhoff

Carsten Eickhoff is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Molecular Biology and Computer Vision and Pattern Recognition, having authored 132 papers that have together received 2.2k indexed citations. Recurring topics across this work include Topic Modeling (35 papers), Information Retrieval and Search Behavior (21 papers), Natural Language Processing Techniques (20 papers), Mobile Crowdsensing and Crowdsourcing (13 papers), Biomedical Text Mining and Ontologies (11 papers), Machine Learning in Healthcare (10 papers), Recommender Systems and Techniques (9 papers) and Web Data Mining and Analysis (8 papers). The work is most often cited by research in Health Informatics (168 citations), Computer Science Applications (394 citations), Artificial Intelligence (835 citations), Information Systems (444 citations) and Management Science and Operations Research (183 citations). Carsten Eickhoff has collaborated with scholars based in United States, Switzerland and Netherlands. Frequent co-authors include Arjen P. de Vries, Thomas Hofmann, Ritambhara Singh, Padmini Srinivasan, Christopher G. Harris, Alexander Meyer, Volkmar Falk, Titus Kühne, Christof Stamm and Jörg Kempfert. Their work appears in journals such as JMIR Medical Education, Journal of Medical Internet Research, Information Retrieval, Scientific Reports and ACM Transactions on Information Systems.

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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