Konstantin Todorov
- Artificial Intelligence
- Information Systems
- Management Science and Operations Research top 10%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Co-authors
- Zohra BellahsènePeter GeibelStefan DietzeElena DemidovaJulian SzymańskiCéline HudelotJohn G. BreslinGiovanni Colavizza
- Topics
- Semantic Web and Ontologies (13 papers)Topic Modeling (9 papers)Data Quality and Management (6 papers)
In The Last Decade
Konstantin Todorov
23 papers receiving 99 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 86
- Information Systems 40
- Management Science and Operations Research 40
- Computer Vision and Pattern Recognition 18
- Molecular Biology 16
Countries citing papers authored by Konstantin Todorov
This map shows the geographic impact of Konstantin Todorov'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 Konstantin Todorov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konstantin Todorov more than expected).
Fields of papers citing papers by Konstantin Todorov
This network shows the impact of papers produced by Konstantin Todorov. 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 Konstantin Todorov. The network helps show where Konstantin Todorov may publish in the future.
Co-authorship network of co-authors of Konstantin Todorov
This figure shows the co-authorship network connecting the top 25 collaborators of Konstantin Todorov. A scholar is included among the top collaborators of Konstantin Todorov 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 Konstantin Todorov. Konstantin Todorov 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 | 2 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | Transfer Learning for Named Entity Recognition in Historical Corpora. | 3 |
| 9 | Modeling and Contextualizing Claims. | 0 |
| 10 | 5 | |
| 11 | 26 | |
| 12 | Legato: Results for OAEI 2017 | 1 |
| 13 | LYAM++ Results for OAEI 2015 | 1 |
| 14 | Datavore: A Vocabulary Recommender Tool Assisting Linked Data Modeling | 2 |
| 15 | 11 | |
| 16 | 3 | |
| 17 | Variable Selection as an Instance-Based Ontology Mapping Strategy. | 3 |
| 18 | 3 | |
| 19 | Ontology mapping via structural and instance-based similarity measures | 6 |
| 20 | 3 |
About Konstantin Todorov
Konstantin Todorov is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 29 papers that have together received 106 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (13 papers), Topic Modeling (9 papers) and Data Quality and Management (6 papers). The work is most often cited by research in Management Science and Operations Research (40 citations), Artificial Intelligence (86 citations) and Information Systems (40 citations). Konstantin Todorov has collaborated with scholars based in France, Germany and Greece. Frequent co-authors include Zohra Bellahsène, Peter Geibel, Stefan Dietze, Elena Demidova, Julian Szymański, Céline Hudelot, John G. Breslin, Giovanni Colavizza, Adrian Popescu and Sofia Kossida. Their work appears in journals such as Frontiers in Immunology, Briefings in Bioinformatics and Multimedia Tools and Applications.
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.