György Móra

1.0k citations
8 papers · 598 indexed · h-index 7
Topics
Biomedical Text Mining and Ontologies (7 papers)Topic Modeling (6 papers)Advanced Text Analysis Techniques (4 papers)
Partner nations
HungaryGermanyJapan

In The Last Decade

György Móra

8 papers receiving 548 citations

Peers

György Móra
Comparison fields: 5 of 52
  • Artificial Intelligence 549
  • Molecular Biology 276
  • Information Systems 39
  • Sociology and Political Science 19
  • Language and Linguistics 11
Replace Olivier Ferret with:
Olivier Ferret France
Roser Morante Belgium
Kevin Humphreys United Kingdom
Ruty Rinott Israel
Lynne M. Fox United States
Mijail Kabadjov Italy
Bruno Bachimont France
Bryan Rink United States
Adeline Nazarenko France
Egoitz Laparra Spain
György Móra relative to Olivier Ferret France Olivier Ferret's profile →
Citations per field
00.5×2.5×
Olivier Ferret · 1×
Citations per year

Countries citing papers authored by György Móra

Since Specialization
Citations

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

Fields of papers citing papers by György Móra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of György Móra

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

All Works

8 of 8 papers shown
#WorkIndexed citations
1 45
2 15
3
Hungarian Dependency Treebank.
50
4
Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
16
5
Linguistic scope-based and biological event-based speculation and negation annotations in the Genia Event and Bio-Scope corpora
4
6
The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text
173
7 13
8 282

About György Móra

György Móra is a scholar working on Artificial Intelligence, Molecular Biology and Infectious Diseases, having authored 8 papers that have together received 598 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Topic Modeling (6 papers) and Advanced Text Analysis Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (549 citations), Molecular Biology (276 citations) and Information Systems (39 citations). György Móra has collaborated with scholars based in Hungary, Germany and Japan. Frequent co-authors include Veronika Vincze, György Szarvas, Richárd Farkas, János Csirik, Iryna Gurevych, Tomoko Ohta and Zsolt Molnár. Their work appears in journals such as BMC Bioinformatics, Computational Linguistics and Language Resources and Evaluation.

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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