Kiril Ribarov

892 citations
7 papers · 569 indexed · 1 hit paper · h-index 3

Kiril Ribarov

4 papers receiving 479 citations

Hit Papers

Non-projective dependency parsing using spanning tree alg...5512005202620122019100200300400500

Peers

Kiril Ribarov
Comparison fields: 5 of 32
  • Artificial Intelligence 552
  • Computational Theory and Mathematics 33
  • Information Systems 44
  • Language and Linguistics 17
  • Computer Vision and Pattern Recognition 30
Replace Jing-Shin Chang with:
Jing-Shin Chang Taiwan
AiTi Aw Singapore
Jorn Veenstra Netherlands
Nicola Cancedda France
Erik F. Tjong Kim Sang Belgium
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Citations per year

Countries citing papers authored by Kiril Ribarov

Since Specialization
Citations

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

Fields of papers citing papers by Kiril Ribarov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 4 scholars most cited alongside Kiril Ribarov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kiril Ribarov Line = papers co-authored together Kiril Ribarov links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
Character Set Standardization for Early Cyrillic Writing after Unicode 5.1
20081
2
When a statistically oriented parser was more efficient than a linguist: A case of treebank conversion.
20062
3
Non-projective dependency parsing using spanning tree algorithmsbreakdown →
2005551
4
Review: Open-Domain Question Answering from Large Text Collections, by Marius Pasca.
20041
5
On the Rule-Based Parsing of Czech
20021
6
Review: Corpus Linguistics. Investigating Language Structure and Use.Cambridge Approaches, by Douglas Biber, Susan Conrad and Randi Reppen.
200112
7
Rule-based Tagging: Morphological Tagset versus Tagset of Analytical Functions
20001

About Kiril Ribarov

Kiril Ribarov is a scholar working on Linguistics and Language, Artificial Intelligence and Language and Linguistics, having authored 7 papers that have together received 569 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (4 papers), Linguistic Variation and Morphology (1 paper), Information Retrieval and Search Behavior (1 paper), Mathematics, Computing, and Information Processing (1 paper), Linguistics, Language Diversity, and Identity (1 paper), linguistics and terminology studies (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Artificial Intelligence (552 citations), Computational Theory and Mathematics (33 citations) and Information Systems (44 citations). Kiril Ribarov has collaborated with scholars based in Czechia and United States. Frequent co-authors include Fernando Pereira, Ryan McDonald, Jan Hajič and Barbora Hladká. Their work appears in journals such as Language Resources and Evaluation and ˜The œPrague Bulletin of Mathematical Linguistics.

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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