Alexander Perekrestenko
- Language and Linguistics top 5%
- Artificial Intelligence
- General Health Professions
- Literature and Literary Theory top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Anthony PymRobert MercaşGemma Bel-Enguix
- Topics
- Translation Studies and Practices (2 papers)DNA and Biological Computing (2 papers)Evolutionary Algorithms and Applications (2 papers)
- Journals
- Procesamiento del lenguaje naturalMinerva Access (University of Melbourne)
In The Last Decade
Alexander Perekrestenko
4 papers receiving 162 citations
Peers
Comparison fields: 5 of 30
- Language and Linguistics 146
- Artificial Intelligence 51
- General Health Professions 36
- Literature and Literary Theory 28
- Experimental and Cognitive Psychology 27
Countries citing papers authored by Alexander Perekrestenko
This map shows the geographic impact of Alexander Perekrestenko'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 Alexander Perekrestenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Perekrestenko more than expected).
Fields of papers citing papers by Alexander Perekrestenko
This network shows the impact of papers produced by Alexander Perekrestenko. 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 Alexander Perekrestenko. The network helps show where Alexander Perekrestenko may publish in the future.
Co-authorship network of co-authors of Alexander Perekrestenko
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Perekrestenko. A scholar is included among the top collaborators of Alexander Perekrestenko 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 Alexander Perekrestenko. Alexander Perekrestenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Networks of Evolutionary Processors as Natural Parsers. | 0 |
| 2 | 1 | |
| 3 | Translation Research Projects 1 | 150 |
| 4 | Explicitation profile and translator style | 14 |
| 5 | A Note on the Complexity of the Recognition Problem for the Minimalist Grammars with Unbounded Scrambling and Barriers | 0 |
| 6 | Translation Technology and its Teaching (with Much Mention of Localization) | 14 |
About Alexander Perekrestenko
Alexander Perekrestenko is a scholar working on Language and Linguistics, Artificial Intelligence and Computational Theory and Mathematics, having authored 6 papers that have together received 179 indexed citations. Recurring topics across this work include Translation Studies and Practices (2 papers), DNA and Biological Computing (2 papers) and Evolutionary Algorithms and Applications (2 papers). The work is most often cited by research in Language and Linguistics (146 citations), Literature and Literary Theory (28 citations) and Communication (15 citations). Alexander Perekrestenko has collaborated with scholars based in Spain and Romania. Frequent co-authors include Anthony Pym, Robert Mercaş and Gemma Bel-Enguix. Their work appears in journals such as Procesamiento del lenguaje natural and Minerva Access (University of Melbourne).
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.