Miloš Stanojević
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience
- Information Systems
- Language and Linguistics
- Co-authors
- Khalil Sima’anOndřej BojarAmir KamranMark SteedmanYvette GrahamPhilipp KoehnJonathan BrennanJohn Hale
- Topics
- Natural Language Processing Techniques (27 papers)Topic Modeling (25 papers)Text Readability and Simplification (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaCognitive ScienceComputational Linguistics
- Partner nations
- NetherlandsUnited KingdomUnited States
In The Last Decade
Miloš Stanojević
28 papers receiving 307 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 314
- Computer Vision and Pattern Recognition 56
- Cognitive Neuroscience 33
- Information Systems 30
- Language and Linguistics 17
Countries citing papers authored by Miloš Stanojević
This map shows the geographic impact of Miloš Stanojević'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 Miloš Stanojević with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miloš Stanojević more than expected).
Fields of papers citing papers by Miloš Stanojević
This network shows the impact of papers produced by Miloš Stanojević. 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 Miloš Stanojević. The network helps show where Miloš Stanojević may publish in the future.
Co-authorship network of co-authors of Miloš Stanojević
This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Stanojević. A scholar is included among the top collaborators of Miloš Stanojević 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 Miloš Stanojević. Miloš Stanojević is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 9 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 10 | |
| 12 | 1 | |
| 13 | Hierarchical Permutation Complexity for Word Order Evaluation | 0 |
| 14 | Universal Reordering via Linguistic Typology | 4 |
| 15 | 3 | |
| 16 | 60 | |
| 17 | 3 | |
| 18 | 18 | |
| 19 | 7 | |
| 20 | Selecting Data for English-to-Czech Machine Translation | 5 |
About Miloš Stanojević
Miloš Stanojević is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Language and Linguistics, having authored 30 papers that have together received 342 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (27 papers), Topic Modeling (25 papers) and Text Readability and Simplification (9 papers). The work is most often cited by research in Artificial Intelligence (314 citations), Computer Vision and Pattern Recognition (56 citations) and Cognitive Neuroscience (33 citations). Miloš Stanojević has collaborated with scholars based in Netherlands, United Kingdom and United States. Frequent co-authors include Khalil Sima’an, Ondřej Bojar, Amir Kamran, Mark Steedman, Yvette Graham, Philipp Koehn, Jonathan Brennan, John Hale, Edward P. Stabler and Joachim Daiber. Their work appears in journals such as SHILAP Revista de lepidopterología, Cognitive Science and Computational Linguistics.
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.