Jan Daciuk

638 total citations
16 papers, 277 citations indexed

About

Jan Daciuk is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Jan Daciuk has authored 16 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 10 papers in Computational Theory and Mathematics and 4 papers in Molecular Biology. Recurrent topics in Jan Daciuk's work include semigroups and automata theory (10 papers), Algorithms and Data Compression (7 papers) and Natural Language Processing Techniques (6 papers). Jan Daciuk is often cited by papers focused on semigroups and automata theory (10 papers), Algorithms and Data Compression (7 papers) and Natural Language Processing Techniques (6 papers). Jan Daciuk collaborates with scholars based in Poland, Netherlands and South Africa. Jan Daciuk's co-authors include Bruce W. Watson, R. E. Watson, Stoyan Mihov, Gertjan van Noord, Mikel L. Forcada, Rafael C. Carrasco, L.J. van der Beek, Robert Malouf, van Gerardus Noord and Gosse Bouma and has published in prestigious journals such as Journal of Experimental Botany, Theoretical Computer Science and Computational Linguistics.

In The Last Decade

Jan Daciuk

16 papers receiving 244 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jan Daciuk Poland 8 242 102 40 25 24 16 277
Mark-Jan Nederhof United Kingdom 11 461 1.9× 183 1.8× 50 1.3× 14 0.6× 25 1.0× 69 507
Atro Voutilainen Finland 11 381 1.6× 36 0.4× 22 0.6× 22 0.9× 54 2.3× 21 440
Kiril Ribarov Czechia 3 552 2.3× 33 0.3× 57 1.4× 30 1.2× 44 1.8× 7 569
Nicola Cancedda France 12 592 2.4× 19 0.2× 40 1.0× 51 2.0× 94 3.9× 34 620
Hiyan Alshawi United States 19 929 3.8× 45 0.4× 41 1.0× 53 2.1× 56 2.3× 44 972
Jonathan Graehl United States 6 880 3.6× 60 0.6× 58 1.4× 141 5.6× 70 2.9× 6 898
AiTi Aw Singapore 11 483 2.0× 17 0.2× 43 1.1× 53 2.1× 53 2.2× 34 514
Jing-Shin Chang Taiwan 11 325 1.3× 25 0.2× 41 1.0× 27 1.1× 39 1.6× 27 350
Bob Carpenter United States 11 350 1.4× 31 0.3× 5 0.1× 21 0.8× 38 1.6× 21 389
Marc Dymetman France 14 637 2.6× 40 0.4× 32 0.8× 66 2.6× 69 2.9× 52 658

Countries citing papers authored by Jan Daciuk

Since Specialization
Citations

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

Fields of papers citing papers by Jan Daciuk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Daciuk

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

All Works

16 of 16 papers shown
1.
Daciuk, Jan. (2014). Optimization of Automata. 1–224. 3 indexed citations
2.
Daciuk, Jan, et al.. (2012). Smaller representation of finite state automata. Theoretical Computer Science. 450. 10–21. 2 indexed citations
3.
Daciuk, Jan, et al.. (2010). NLP Dictionaries Implemented as FSAs. 1 indexed citations
4.
Carrasco, Rafael C., Jan Daciuk, & Mikel L. Forcada. (2008). Incremental Construction of Minimal Tree Automata. Algorithmica. 55(1). 95–110. 8 indexed citations
5.
6.
Watson, Bruce W. & Jan Daciuk. (2003). An efficient incremental DFA minimization algorithm. Natural Language Engineering. 9(1). 49–64. 26 indexed citations
7.
Daciuk, Jan & Gertjan van Noord. (2003). Finite automata for compact representation of tuple dictionaries. Theoretical Computer Science. 313(1). 45–56. 4 indexed citations
8.
9.
Beek, L.J. van der, et al.. (2002). Algorithms for Linguistic Processing, NWO PIONIER, Progress Report. Data Archiving and Networked Services (DANS). 8 indexed citations
10.
Daciuk, Jan. (2001). Treatment of Unknown Words. Lecture notes in computer science. 71–80. 2 indexed citations
11.
Daciuk, Jan. (2001). Computer-Assisted Enlargement of Morphological Dictionaries. Data Archiving and Networked Services (DANS). 23–27. 1 indexed citations
12.
Daciuk, Jan, Stoyan Mihov, Bruce W. Watson, & R. E. Watson. (2000). Incremental Construction of Minimal Acyclic Finite-State Automata. Computational Linguistics. 26(1). 3–16. 87 indexed citations
13.
Daciuk, Jan. (2000). Finite State Tools for Natural Language Processing. Data Archiving and Networked Services (DANS). 34–37. 8 indexed citations
14.
Daciuk, Jan. (2000). The 18th International Conference on Computational Linguistics. 82 indexed citations
15.
Beek, L.J. van der, et al.. (1999). Algorithms for Linguistic Processing. Journal of Experimental Botany. 74(7). 2416–2432. 5 indexed citations
16.
Daciuk, Jan, Bruce W. Watson, & R. E. Watson. (1998). Incremental construction of minimal acyclic finite state automata and transducers. 48–56. 28 indexed citations

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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