Dmitry I. Ignatov

1.7k total citations
85 papers, 692 citations indexed

About

Dmitry I. Ignatov is a scholar working on Information Systems, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Dmitry I. Ignatov has authored 85 papers receiving a total of 692 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Information Systems, 28 papers in Artificial Intelligence and 26 papers in Computational Theory and Mathematics. Recurrent topics in Dmitry I. Ignatov's work include Rough Sets and Fuzzy Logic (26 papers), Data Mining Algorithms and Applications (19 papers) and Data Management and Algorithms (10 papers). Dmitry I. Ignatov is often cited by papers focused on Rough Sets and Fuzzy Logic (26 papers), Data Mining Algorithms and Applications (19 papers) and Data Management and Algorithms (10 papers). Dmitry I. Ignatov collaborates with scholars based in Russia, United States and Germany. Dmitry I. Ignatov's co-authors include Sergei O. Kuznetsov, Jonas Poelmans, Guido Dedene, Muhammad Shahid Iqbal Malik, A. Savchenko, Boris Mirkin, Mona Jamjoom, Pavel Braslavski, Yana Volkovich and Leonid Zhukov and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Dmitry I. Ignatov

71 papers receiving 657 citations

Peers

Dmitry I. Ignatov
Suge Wang China
Gholamreza Nakhaeizadeh Germany
Vikram Pudi India
Hayato Yamana Japan
Sabbir M. Rashid United States
Pieter Adriaans Netherlands
Iryna Yevseyeva United Kingdom
Axel Polleres Chile
José Emilio Labra Gayo Chile
Lukas Schmelzeisen Chile
Suge Wang China
Dmitry I. Ignatov
Citations per year, relative to Dmitry I. Ignatov Dmitry I. Ignatov (= 1×) peers Suge Wang

Countries citing papers authored by Dmitry I. Ignatov

Since Specialization
Citations

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

Fields of papers citing papers by Dmitry I. Ignatov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dmitry I. Ignatov. 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 Dmitry I. Ignatov. The network helps show where Dmitry I. Ignatov may publish in the future.

Co-authorship network of co-authors of Dmitry I. Ignatov

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

All Works

20 of 20 papers shown
1.
Braslavski, Pavel, et al.. (2025). TimeGPT’s Potential in Cryptocurrency Forecasting: Efficiency, Accuracy, and Economic Value. Forecasting. 7(3). 48–48. 1 indexed citations
2.
Braslavski, Pavel, et al.. (2025). Bitcoin Ordinals: Bitcoin Price and Transaction Fee Rate Predictions. IEEE Access. 13. 35478–35489. 2 indexed citations
3.
Malik, Muhammad Shahid Iqbal, et al.. (2024). Categorization of tweets for damages: infrastructure and human damage assessment using fine-tuned BERT model. PeerJ Computer Science. 10. e1859–e1859. 9 indexed citations
4.
Malik, Muhammad Shahid Iqbal, et al.. (2024). Deepthreatexplainer: a united explainable predictor for threat comments identification on Twitter. Social Network Analysis and Mining. 14(1).
5.
Ignatov, Dmitry I., et al.. (2024). Development of a questionnaire for assessing the functions informal subgroups perform in relation to the work group. Psikhologicheskii zhurnal. 45(2). 80–90.
6.
7.
Ignatov, Dmitry I., et al.. (2023). Identifying dyslexia in school pupils from eye movement and demographic data using artificial intelligence. PLoS ONE. 18(11). e0292047–e0292047. 8 indexed citations
8.
Ignatov, Dmitry I., et al.. (2019). Searching for Interpretable Demographic Patterns. Munich Personal RePEc Archive (Munich University). 18–31. 1 indexed citations
9.
Ignatov, Dmitry I., et al.. (2019). Attribution of Customers’ Actions Based on Machine Learning Approach. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 77–88. 1 indexed citations
10.
Ignatov, Dmitry I., et al.. (2018). Understanding Collaborative Filtering with Galois Connections.. International Joint Conference on Artificial Intelligence. 127–143. 1 indexed citations
11.
Ignatov, Dmitry I., et al.. (2017). Behavior Mining in h-index Ranking Game. MPRA Paper. 52–64. 2 indexed citations
12.
Ignatov, Dmitry I., et al.. (2016). What is a Fair Value of Your Recommendation List. RePEc: Research Papers in Economics. 1–12. 1 indexed citations
13.
Ignatov, Dmitry I., et al.. (2016). A Lattice-based Consensus Clustering Algorithm. 45–56.
14.
Khachay, Michael, et al.. (2016). Analysis of Images, Social Networks and Texts: 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9-11, 2015. Springer eBooks.
15.
Zudin, Sergey, et al.. (2015). Putting OAC-triclustering on MapReduce. 47–58. 3 indexed citations
16.
Ignatov, Dmitry I., et al.. (2014). A One-Pass Triclustering Approach: Is There any Room for Big Data?. 231–242. 5 indexed citations
17.
Ignatov, Dmitry I., et al.. (2014). Analysis of Images, Social Networks and Texts: Third International Conference, AIST 2014, Yekaterinburg, Russia, April 10-12, 2014, Revised Selected. Springer eBooks. 1 indexed citations
18.
Ignatov, Dmitry I., et al.. (2013). From Triadic FCA to Triclustering: Experimental Comparison of Some Triclustering Algorithms. 249–260. 11 indexed citations
19.
Ignatov, Dmitry I., et al.. (2011). What can closed sets of students and their marks say. Educational Data Mining. 223–228. 6 indexed citations
20.
Ignatov, Dmitry I., et al.. (2011). How university entrants are choosing their department? Mining of university admission process with FCA taxonomies. Educational Data Mining. 229–234. 3 indexed citations

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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