Andrei Mikheev
Impact in
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
- Semantic Web and Ontologies
- Speech and dialogue systems
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
- Information Systems top 5%
- Web Data Mining and Analysis
Papers in
-
- Natural Language Processing Techniques 16
- Topic Modeling 14
- Speech and dialogue systems 5
- Semantic Web and Ontologies 4
- Algorithms and Data Compression 4
-
- Data Mining Algorithms and Applications 2
- Journals
- Computational Linguistics (2 papers)Natural Language Engineering (2 papers)Language Resources and Evaluation (1 paper)The COCOON platform (University of Paris) (1 paper)Edinburgh Research Explorer (University of Edinburgh) (1 paper)
- Partner nations
- United KingdomUnited StatesRussia
In The Last Decade
Andrei Mikheev
17 papers receiving 678 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 768
- Information Systems 149
- Geography, Planning and Development 35
- Management Science and Operations Research 61
- Signal Processing 46
Countries citing papers authored by Andrei Mikheev
This map shows the geographic impact of Andrei Mikheev'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 Andrei Mikheev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrei Mikheev more than expected).
Fields of papers citing papers by Andrei Mikheev
This network shows the impact of papers produced by Andrei Mikheev. 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 Andrei Mikheev. The network helps show where Andrei Mikheev may publish in the future.
Co-authorship network
The 5 scholars most cited alongside Andrei Mikheev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 57 | |
| 2 | LT TTT - A Flexible Tokenisation Tool | 2000 | 72 |
| 3 | Tagging sentence boundaries | 2000 | 32 |
| 4 | 2000 | 32 | |
| 5 | 1999 | 257 | |
| 6 | 1999 | 18 | |
| 7 | 1999 | 35 | |
| 8 | Description of the LTG system used for MUC-7 | 1998 | 107 |
| 9 | 1998 | 25 | |
| 10 | 1998 | 14 | |
| 11 | Automatic rule induction for unknown-word guessing | 1997 | 121 |
| 12 | 1997 | 41 | |
| 13 | 1996 | 2 | |
| 14 | 1996 | 15 | |
| 15 | 1996 | 8 | |
| 16 | 1995 | 12 | |
| 17 | 1995 | 11 |
About Andrei Mikheev
Andrei Mikheev is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Cultural Studies and Infectious Diseases, having authored 17 papers that have together received 859 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (16 papers), Topic Modeling (14 papers), Speech and dialogue systems (5 papers), Semantic Web and Ontologies (4 papers), Algorithms and Data Compression (4 papers), Data Mining Algorithms and Applications (2 papers), Mathematics, Computing, and Information Processing (1 paper) and Language and cultural evolution (1 paper). The work is most often cited by research in Artificial Intelligence (768 citations), Information Systems (149 citations), Geography, Planning and Development (35 citations), Management Science and Operations Research (61 citations) and Signal Processing (46 citations). Andrei Mikheev has collaborated with scholars based in United Kingdom, United States and Russia. Frequent co-authors include Marc Moens, Claire Grover, Steven Finch, Colin Matheson and Massimo Poesio. Their work appears in journals such as Computational Linguistics, Natural Language Engineering, Language Resources and Evaluation, The COCOON platform (University of Paris) and Edinburgh Research Explorer (University of Edinburgh).
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.