Atanas Chanev

843 citations
2 papers · 510 indexed · 1 hit paper · h-index 2
Topics
Natural Language Processing Techniques (2 papers)Topic Modeling (2 papers)Speech and dialogue systems (1 paper)
Journals
Natural Language EngineeringCINECA IRIS Institutial research information system (University of Pisa)
Partner nations
SwedenItalyGermany

In The Last Decade

Atanas Chanev

2 papers receiving 442 citations

Hit Papers

MaltParser: A language-independent system for data-driven...20072026201320192007100200300400

Peers

Atanas Chanev
Comparison fields: 5 of 34
  • Artificial Intelligence 496
  • Information Systems 46
  • Molecular Biology 30
  • Computer Vision and Pattern Recognition 29
  • Language and Linguistics 27
Replace Svetoslav Marinov with:
Svetoslav Marinov Sweden
Lane Schwartz United States
António Branco Portugal
Katri Haverinen Finland
Felipe Sánchez-Martínez Spain
Ondřej Dušek Czechia
Yannick Versley Germany
Kyoko Kanzaki Japan
Anna Feldman United States
Gema Ramírez-Sánchez Spain
Atanas Chanev relative to Svetoslav Marinov Sweden Svetoslav Marinov's profile →
Citations per field
00.5×1.5×
Svetoslav Marinov · 1×
Citations per year

Countries citing papers authored by Atanas Chanev

Since Specialization
Citations

This map shows the geographic impact of Atanas Chanev'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 Atanas Chanev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Atanas Chanev more than expected).

Fields of papers citing papers by Atanas Chanev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Atanas Chanev. 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 Atanas Chanev. The network helps show where Atanas Chanev may publish in the future.

Co-authorship network of co-authors of Atanas Chanev

This figure shows the co-authorship network connecting the top 25 collaborators of Atanas Chanev. A scholar is included among the top collaborators of Atanas Chanev 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 Atanas Chanev. Atanas Chanev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

2 of 2 papers shown
#WorkIndexed citations
1
Multilingual Dependency Parsing and Domain Adaptation using DeSR
29
2
MaltParser: A language-independent system for data-driven dependency parsingbreakdown →
481

About Atanas Chanev

Atanas Chanev is a scholar working on Artificial Intelligence, Information Systems and Infectious Diseases, having authored 2 papers that have together received 510 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (2 papers), Topic Modeling (2 papers) and Speech and dialogue systems (1 paper). The work is most often cited by research in Artificial Intelligence (496 citations), Language and Linguistics (27 citations) and Information Systems (46 citations). Atanas Chanev has collaborated with scholars based in Sweden, Italy and Germany. Frequent co-authors include Joakim Nivre, Gülşen Eryiğit, Sandra Kübler, Svetoslav Marinov, Johan Hall, Jens Nilsson, Erwin Marsi, Maria Simi, Felice Dell’Orletta⋄ and Giuseppe Attardi. Their work appears in journals such as Natural Language Engineering and CINECA IRIS Institutial research information system (University of Pisa).

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.

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