Danil Nemirovsky
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Information Systems top 10%
- Web Data Mining and Analysis
Papers in
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- Web Data Mining and Analysis 5
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- Complex Network Analysis Techniques 3
- Co-authors
- Konstantin Avrachenkov (8 shared papers)Nelly Litvak (1 shared paper)Elena Smirnova (1 shared paper)Son Pham (1 shared paper)Vivek S. Borkar (1 shared paper)
- Journals
- Journal of Computational and Applied Mathematics (1 paper)Linear Algebra and its Applications (1 paper)SIAM Journal on Numerical Analysis (1 paper)University of Twente Research Information (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- FranceRussiaUnited States
In The Last Decade
Danil Nemirovsky
9 papers receiving 176 citations
Peers
Comparison fields: 5 of 35
- Statistical and Nonlinear Physics 91
- Information Systems 65
- Computer Networks and Communications 62
- Artificial Intelligence 86
- Signal Processing 25
Countries citing papers authored by Danil Nemirovsky
This map shows the geographic impact of Danil Nemirovsky'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 Danil Nemirovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danil Nemirovsky more than expected).
Fields of papers citing papers by Danil Nemirovsky
This network shows the impact of papers produced by Danil Nemirovsky. 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 Danil Nemirovsky. The network helps show where Danil Nemirovsky may publish in the future.
Co-authors
The 5 scholars most cited alongside Danil Nemirovsky, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 137 | |
| 2 | 2008 | 17 | |
| 3 | 2007 | 9 | |
| 4 | 2007 | 8 | |
| 5 | Weighted PageRank: Cluster-Related Weights | 2008 | 7 |
| 6 | 2010 | 7 | |
| 7 | Monte Carlo methods in PageRank computation: When one iteration is sufficient | 2005 | 2 |
| 8 | Word Importance Discrimination using Context Information | 2008 | 1 |
| 9 | 2006 | 1 | |
| 10 | 2011 | 0 |
About Danil Nemirovsky
Danil Nemirovsky is a scholar working on Information Systems, Statistical and Nonlinear Physics, Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 10 papers that have together received 189 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (5 papers), Complex Network Analysis Techniques (3 papers), Data Management and Algorithms (3 papers), Cryptography and Data Security (2 papers), Natural Language Processing Techniques (1 paper), Caching and Content Delivery (1 paper), Cooperative Communication and Network Coding (1 paper) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (91 citations), Information Systems (65 citations), Computer Networks and Communications (62 citations), Artificial Intelligence (86 citations) and Signal Processing (25 citations). Danil Nemirovsky has collaborated with scholars based in France, Russia and United States. Frequent co-authors include Konstantin Avrachenkov, Nelly Litvak, Elena Smirnova, Son Pham and Vivek S. Borkar. Their work appears in journals such as Journal of Computational and Applied Mathematics, Linear Algebra and its Applications, SIAM Journal on Numerical Analysis, University of Twente Research Information and HAL (Le Centre pour la Communication Scientifique Directe).
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.