Tjitze Rienstra

401 citations
34 papers · 274 · h-index 10

Impact in

Papers in

Tjitze Rienstra

28 papers receiving 257 citations

Peers

Tjitze Rienstra
Comparison fields: 5 of 23
  • Artificial Intelligence 269
  • Management Information Systems 33
  • Information Systems 20
  • Health Informatics 1
  • Sociology and Political Science 29
Replace Sylvie Doutre with:
Sylvie Doutre France
Nico Potyka Germany
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Bartosz Broda Poland
Anuj Mahajan India
Kristijonas Čyras United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Tjitze Rienstra

Since Specialization
Citations

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

Fields of papers citing papers by Tjitze Rienstra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Tjitze Rienstra, 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 Tjitze Rienstra Line = papers co-authored together Tjitze Rienstra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Opponent models with uncertainty for strategic argumentation
201364
2
Towards a probabilistic Dung-style argumentation system ?
201239
3 201335
4 201514
5 201410
6 202010
7 202010
8 201210
9 20179
10 20129
11
Probabilistic Abstract Argumentation Based on SCC Decomposability
20188
12 20208
13 20217
14 20126
15 20204
16 20184
17 20204
18 20134
19 20213
20 20202

About Tjitze Rienstra

Tjitze Rienstra is a scholar working on Artificial Intelligence, Management Information Systems, Information Systems, Signal Processing and Computer Networks and Communications, having authored 34 papers that have together received 274 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (25 papers), Multi-Agent Systems and Negotiation (24 papers), Semantic Web and Ontologies (19 papers), Bayesian Modeling and Causal Inference (6 papers), Business Process Modeling and Analysis (4 papers), Topic Modeling (2 papers), Service-Oriented Architecture and Web Services (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (269 citations), Management Information Systems (33 citations), Information Systems (20 citations), Health Informatics (1 citation) and Sociology and Political Science (29 citations). Tjitze Rienstra has collaborated with scholars based in Germany, Luxembourg and Netherlands. Frequent co-authors include Matthias Thimm, Leendert van der Torre, Nir Oren, Richard Booth, Souhila Kaci, Chiaki Sakama, Beishui Liao, Steffen Staab, François Schwarzentruber and Srdjan Vesić. Their work appears in journals such as Lecture notes in computer science, Artificial Intelligence, International Journal of Medical Informatics, Fundamenta Informaticae and Frontiers in artificial intelligence and applications.

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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