Igor Boguslavsky
- Artificial Intelligence top 5%
- Language and Linguistics top 10%
- Molecular Biology
- Information Systems
- Computer Vision and Pattern Recognition
- Topics
- Natural Language Processing Techniques (18 papers)Topic Modeling (7 papers)Lexicography and Language Studies (6 papers)
In The Last Decade
Igor Boguslavsky
21 papers receiving 188 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 210
- Language and Linguistics 36
- Molecular Biology 15
- Information Systems 12
- Computer Vision and Pattern Recognition 10
Countries citing papers authored by Igor Boguslavsky
This map shows the geographic impact of Igor Boguslavsky'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 Igor Boguslavsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor Boguslavsky more than expected).
Fields of papers citing papers by Igor Boguslavsky
This network shows the impact of papers produced by Igor Boguslavsky. 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 Igor Boguslavsky. The network helps show where Igor Boguslavsky may publish in the future.
Co-authorship network of co-authors of Igor Boguslavsky
This figure shows the co-authorship network connecting the top 25 collaborators of Igor Boguslavsky. A scholar is included among the top collaborators of Igor Boguslavsky 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 Igor Boguslavsky. Igor Boguslavsky 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | Emotion and Inner State Adverbials in Russian | 1 |
| 7 | Argument structure of adverbial derivatives in Russian | 1 |
| 8 | 62 | |
| 9 | 11 | |
| 10 | Semantic analysis based on linguistic and ontological resources | 5 |
| 11 | Semantics of attenuated comparatives in Russian | 1 |
| 12 | Universal Dictionary of Concepts | 2 |
| 13 | 4 | |
| 14 | A Syntactically and Semantically Tagged Corpus of Russian: State of the Art and Prospects | 25 |
| 15 | Interactive Enconversion by Means of the Etap-3 System | 5 |
| 16 | Some Controversial Issues of UNL: Linguistic Aspects | 2 |
| 17 | Some Lexical Issues of UNL | 3 |
| 18 | 4 | |
| 19 | Development of a Dependency Treebank for Russian and its Possible Applications in NLP | 24 |
| 20 | 28 |
About Igor Boguslavsky
Igor Boguslavsky is a scholar working on General Social Sciences, Artificial Intelligence and Language and Linguistics, having authored 27 papers that have together received 234 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (7 papers) and Lexicography and Language Studies (6 papers). The work is most often cited by research in Artificial Intelligence (210 citations), Language and Linguistics (36 citations) and General Social Sciences (5 citations). Igor Boguslavsky has collaborated with scholars based in Russia, Spain and Sweden. Frequent co-authors include Joakim Nivre, Bernd Bohnet, Filip Ginter, Jan Hajič and Richárd Farkas. Their work appears in journals such as Applied Linguistics, Language Resources and Evaluation 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.