Marco Kuhlmann

1.9k total citations
62 papers, 914 citations indexed

About

Marco Kuhlmann is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Marco Kuhlmann has authored 62 papers receiving a total of 914 indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 21 papers in Computational Theory and Mathematics and 5 papers in Molecular Biology. Recurrent topics in Marco Kuhlmann's work include Natural Language Processing Techniques (54 papers), Topic Modeling (31 papers) and semigroups and automata theory (21 papers). Marco Kuhlmann is often cited by papers focused on Natural Language Processing Techniques (54 papers), Topic Modeling (31 papers) and semigroups and automata theory (21 papers). Marco Kuhlmann collaborates with scholars based in Sweden, Germany and Italy. Marco Kuhlmann's co-authors include Giorgio Satta, Stephan Oepen, Joakim Nivre, Carlos Gómez‐Rodríguez, Alexander Koller, Dan Flickinger, Daniel Zeman, Yusuke Miyao, Jan Hajič and Zdeňka Urešová and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Computer and System Sciences and Computational Linguistics.

In The Last Decade

Marco Kuhlmann

58 papers receiving 811 citations

Peers

Marco Kuhlmann
Comparison fields: 5 of 65
  • Artificial Intelligence 867
  • Computational Theory and Mathematics 163
  • Molecular Biology 84
  • Computer Vision and Pattern Recognition 48
  • Language and Linguistics 45
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Citations per field, relative to Marco Kuhlmann
Marco Kuhlmann · 1×
Citations per year, relative to Marco Kuhlmann
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Countries citing papers authored by Marco Kuhlmann

Since Specialization
Citations

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

Fields of papers citing papers by Marco Kuhlmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Kuhlmann

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Kuhlmann. A scholar is included among the top collaborators of Marco Kuhlmann 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 Marco Kuhlmann. Marco Kuhlmann 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
# Work Indexed citations
1 4
2 2
3 2
4
Exploiting Structure in Parsing to 1-Endpoint-Crossing Graphs
2
5
Towards a Standard Dataset of Swedish Word Vectors
4
6
Towards Comparability of Linguistic Graph Banks for Semantic Parsing
24
7 8
8
Decomposing TAG Parsing Algorithms Using Simple Algebraizations
0
9
A Generalized View on Parsing and Translation
25
10
Dynamic Programming Algorithms for Transition-Based Dependency Parsers
62
11 11
12
Efficient Parsing of Well-Nested Linear Context-Free Rewriting Systems
26
13
Proceedings of the 2010 Workshop on Applications of Tree Automata in Natural Language Processing
2
14
The Importance of Rule Restrictions in CCG
5
15 24
16 33
17
Mildly Context-Sensitive Dependency Languages
20
18 3
19 2
20 1

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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