Marina Danilevsky
- Artificial Intelligence top 2%
- Statistical and Nonlinear Physics top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Topics
- Topic Modeling (11 papers)Advanced Text Analysis Techniques (9 papers)Natural Language Processing Techniques (8 papers)
- Journals
- Proceedings of the VLDB EndowmentKnowledge and Information SystemsTransactions of the Association for Computational Linguistics
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Marina Danilevsky
34 papers receiving 691 citations
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 547
- Statistical and Nonlinear Physics 152
- Information Systems 143
- Computer Vision and Pattern Recognition 75
- Computer Networks and Communications 46
Countries citing papers authored by Marina Danilevsky
This map shows the geographic impact of Marina Danilevsky'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 Marina Danilevsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marina Danilevsky more than expected).
Fields of papers citing papers by Marina Danilevsky
This network shows the impact of papers produced by Marina Danilevsky. 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 Marina Danilevsky. The network helps show where Marina Danilevsky may publish in the future.
Co-authorship network of co-authors of Marina Danilevsky
This figure shows the co-authorship network connecting the top 25 collaborators of Marina Danilevsky. A scholar is included among the top collaborators of Marina Danilevsky 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 Marina Danilevsky. Marina Danilevsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 7 | |
| 4 | 5 | |
| 5 | 79 | |
| 6 | 6 | |
| 7 | 103 | |
| 8 | Multilingual Information Extraction with PolyglotIE | 5 |
| 9 | 1 | |
| 10 | 13 | |
| 11 | Large-scale spectral clustering on graphs | 43 |
| 12 | Entity Role Discovery in Hierarchical Topical Communities | 4 |
| 13 | 13 | |
| 14 | 4 | |
| 15 | Locality Preserving Feature Learning | 7 |
| 16 | 4 | |
| 17 | 4 | |
| 18 | 25 | |
| 19 | 2 | |
| 20 | 16 |
About Marina Danilevsky
Marina Danilevsky is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics, having authored 38 papers that have together received 722 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Advanced Text Analysis Techniques (9 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (547 citations), Statistical and Nonlinear Physics (152 citations) and Health Informatics (15 citations). Marina Danilevsky has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Jiawei Han, Ji Ming, Chi Wang, Ranit Aharonov, Yannis Katsis, Kun Qian, Prithviraj Sen, Ban Kawas, Jialu Liu and Laura Chiticariu. Their work appears in journals such as Proceedings of the VLDB Endowment, Knowledge and Information Systems and Transactions of the Association for 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.