Maxim Mozgovoy
- Artificial Intelligence top 5%
- Information Systems top 5%
- Safety Research top 5%
- Developmental and Educational Psychology top 10%
- Computer Science Applications top 5%
- Co-authors
- Tuomo KakkonenErkki SutinenMyriam MunezeroCalkin Suero MonteroJohn BlakeKimmo FredrikssonGeorgina CosmaVitaly Klyuev
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (8 papers)Artificial Intelligence in Games (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaApplied SciencesJournal of Educational Computing Research
In The Last Decade
Maxim Mozgovoy
47 papers receiving 418 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 241
- Information Systems 141
- Safety Research 100
- Developmental and Educational Psychology 79
- Computer Science Applications 65
Countries citing papers authored by Maxim Mozgovoy
This map shows the geographic impact of Maxim Mozgovoy'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 Maxim Mozgovoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxim Mozgovoy more than expected).
Fields of papers citing papers by Maxim Mozgovoy
This network shows the impact of papers produced by Maxim Mozgovoy. 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 Maxim Mozgovoy. The network helps show where Maxim Mozgovoy may publish in the future.
Co-authorship network of co-authors of Maxim Mozgovoy
This figure shows the co-authorship network connecting the top 25 collaborators of Maxim Mozgovoy. A scholar is included among the top collaborators of Maxim Mozgovoy 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 Maxim Mozgovoy. Maxim Mozgovoy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | Plagiarism Detection Systems for Programming Assignments: Practical Considerations | 0 |
| 4 | 12 | |
| 5 | So You Want to Build a Farm: An Approach to Resource and Time Consuming Testing of Mobile Applications | 0 |
| 6 | 8 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | Using Image Recognition for Testing Hand-drawn Graphic User Interfaces | 4 |
| 10 | 3 | |
| 11 | 6 | |
| 12 | 3 | |
| 13 | Antisocial Behavior corpus for harmful language detection | 8 |
| 14 | Towards WordBricks — A virtual language lab for computer-assisted language learning | 4 |
| 15 | 5 | |
| 16 | Dependency-based rules for grammar checking with LanguageTool | 9 |
| 17 | Grammar Checking with Dependency Parsing: A Possible Extension for LanguageTool | 1 |
| 18 | 3 | |
| 19 | Enhancing Computer-Aided Plagiarism Detection | 14 |
| 20 | 20 |
About Maxim Mozgovoy
Maxim Mozgovoy is a scholar working on Software, Artificial Intelligence and Computer Science Applications, having authored 50 papers that have together received 464 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Artificial Intelligence in Games (8 papers). The work is most often cited by research in Computer Science Applications (65 citations), Safety Research (100 citations) and Artificial Intelligence (241 citations). Maxim Mozgovoy has collaborated with scholars based in Japan, Finland and Russia. Frequent co-authors include Tuomo Kakkonen, Erkki Sutinen, Myriam Munezero, Calkin Suero Montero, John Blake, Kimmo Fredriksson, Georgina Cosma, Vitaly Klyuev, Hiroshi Yamaguchi and Jeremy Perkins. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Sciences and Journal of Educational Computing Research.
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.