Yulia Ledeneva
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Advanced Text Analysis Techniques
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- Sentiment Analysis and Opinion Mining
- Edcuational Technology Systems
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- Web Data Mining and Analysis
Papers in
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- Advanced Text Analysis Techniques 20
- Topic Modeling 20
- Natural Language Processing Techniques 15
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- Web Data Mining and Analysis 5
- Co-authors
- René Arnulfo García-Hernández (17 shared papers)Sergio Díaz (1 shared paper)Carlos Gutiérrez (1 shared paper)Alexander Gelbukh (1 shared paper)Carlos A. Reyes-García (1 shared paper)Mikhail Alexandrov (1 shared paper)
In The Last Decade
Yulia Ledeneva
27 papers receiving 177 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 178
- Information Systems 28
- Computer Vision and Pattern Recognition 10
- Computer Science Applications 2
- Media Technology 3
Countries citing papers authored by Yulia Ledeneva
This map shows the geographic impact of Yulia Ledeneva'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 Yulia Ledeneva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yulia Ledeneva more than expected).
Fields of papers citing papers by Yulia Ledeneva
This network shows the impact of papers produced by Yulia Ledeneva. 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 Yulia Ledeneva. The network helps show where Yulia Ledeneva may publish in the future.
Co-authors
The 6 scholars most cited alongside Yulia Ledeneva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 36 | |
| 2 | 2009 | 35 | |
| 3 | 2018 | 31 | |
| 4 | 2021 | 19 | |
| 5 | 2018 | 12 | |
| 6 | 2009 | 8 | |
| 7 | 2014 | 7 | |
| 8 | 2019 | 6 | |
| 9 | 2020 | 5 | |
| 10 | 2018 | 5 | |
| 11 | 2023 | 4 | |
| 12 | 2018 | 4 | |
| 13 | 2020 | 4 | |
| 14 | Recent Advances in Computational Linguistics | 2010 | 3 |
| 15 | 2020 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2020 | 2 | |
| 18 | 2023 | 2 | |
| 19 | Experimenting with Maximal Frequent Sequences for Multi-Document Summarization | 2010 | 1 |
| 20 | 2020 | 1 |
About Yulia Ledeneva
Yulia Ledeneva is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 30 papers that have together received 196 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (20 papers), Topic Modeling (20 papers), Natural Language Processing Techniques (15 papers), Web Data Mining and Analysis (5 papers), Computational Drug Discovery Methods (2 papers), Handwritten Text Recognition Techniques (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Image Processing and 3D Reconstruction (1 paper). The work is most often cited by research in Artificial Intelligence (178 citations), Information Systems (28 citations), Computer Vision and Pattern Recognition (10 citations), Computer Science Applications (2 citations) and Media Technology (3 citations). Yulia Ledeneva has collaborated with scholars based in Mexico, Spain and Russia. Frequent co-authors include René Arnulfo García-Hernández, Sergio Díaz, Carlos Gutiérrez, Alexander Gelbukh, Carlos A. Reyes-García and Mikhail Alexandrov. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, IEEE Access, Computer Speech & Language, Expert Systems with Applications and Journal of Applied Research and Technology.
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.