Aleksandr Vorobev
- Artificial Intelligence
- Information Systems
- Management Science and Operations Research
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Gleb GusevPavel SerdyukovLiudmila ProkhorenkovaN. KazeevEugene KharitonovIadh OunisCraig Macdonald
- Topics
- Machine Learning and Data Classification (2 papers)Big Data and Business Intelligence (1 paper)Advanced Data Processing Techniques (1 paper)
- Journals
- SHILAP Revista de lepidopterologíaScientific and Technical Information ProcessingENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)
- Partner nations
- RussiaUnited Kingdom
In The Last Decade
Aleksandr Vorobev
5 papers receiving 54 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 18
- Information Systems 15
- Management Science and Operations Research 13
- Computer Networks and Communications 11
- Electrical and Electronic Engineering 8
Countries citing papers authored by Aleksandr Vorobev
This map shows the geographic impact of Aleksandr Vorobev'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 Aleksandr Vorobev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aleksandr Vorobev more than expected).
Fields of papers citing papers by Aleksandr Vorobev
This network shows the impact of papers produced by Aleksandr Vorobev. 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 Aleksandr Vorobev. The network helps show where Aleksandr Vorobev may publish in the future.
Co-authorship network of co-authors of Aleksandr Vorobev
This figure shows the co-authorship network connecting the top 25 collaborators of Aleksandr Vorobev. A scholar is included among the top collaborators of Aleksandr Vorobev 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 Aleksandr Vorobev. Aleksandr Vorobev 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 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | Learning to select for a predefined ranking | 2 |
| 6 | Fighting biases with dynamic boosting. | 24 |
| 7 | 14 | |
| 8 | 13 |
About Aleksandr Vorobev
Aleksandr Vorobev is a scholar working on Computer Science Applications, Management Science and Operations Research and Management Information Systems, having authored 8 papers that have together received 56 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (2 papers), Big Data and Business Intelligence (1 paper) and Advanced Data Processing Techniques (1 paper). The work is most often cited by research in Management Science and Operations Research (13 citations), Computer Science Applications (5 citations) and Information Systems (15 citations). Aleksandr Vorobev has collaborated with scholars based in Russia and United Kingdom. Frequent co-authors include Gleb Gusev, Pavel Serdyukov, Liudmila Prokhorenkova, N. Kazeev, Eugene Kharitonov, Iadh Ounis and Craig Macdonald. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific and Technical Information Processing and ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam).
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.