Maxim Mozgovoy

861 citations
50 papers · 464 indexed · h-index 12

Maxim Mozgovoy

47 papers receiving 418 citations

Peers

Maxim Mozgovoy
Comparison fields: 5 of 70
  • Computer Science Applications 65
  • Safety Research 100
  • Artificial Intelligence 241
  • Information Systems 141
  • Developmental and Educational Psychology 79
Replace Panagiotis Zervas with:
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Citations per year

Countries citing papers authored by Maxim Mozgovoy

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 18 scholars most cited alongside Maxim Mozgovoy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maxim Mozgovoy Line = papers co-authored together Maxim Mozgovoy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20244
2 20231
3
Plagiarism Detection Systems for Programming Assignments: Practical Considerations
20200
4 202012
5
So You Want to Build a Farm: An Approach to Resource and Time Consuming Testing of Mobile Applications
20180
6 20188
7 20182
8 20182
9
Using Image Recognition for Testing Hand-drawn Graphic User Interfaces
20174
10 20163
11 20166
12 20153
13
Antisocial Behavior corpus for harmful language detection
20138
14
Towards WordBricks — A virtual language lab for computer-assisted language learning
20124
15 20125
16
Dependency-based rules for grammar checking with LanguageTool
20119
17
Grammar Checking with Dependency Parsing: A Possible Extension for LanguageTool
20111
18 20103
19
Enhancing Computer-Aided Plagiarism Detection
200814
20 200720

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), Artificial Intelligence in Games (8 papers), Sports Analytics and Performance (7 papers), Speech and dialogue systems (6 papers), Academic integrity and plagiarism (6 papers), Educational Games and Gamification (5 papers) and Multi-Agent Systems and Negotiation (4 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.

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