Etsuji Tomita

2.0k total citations · 1 hit paper
47 papers, 818 citations indexed

About

Etsuji Tomita is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Etsuji Tomita has authored 47 papers receiving a total of 818 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computational Theory and Mathematics, 28 papers in Artificial Intelligence and 14 papers in Molecular Biology. Recurrent topics in Etsuji Tomita's work include Algorithms and Data Compression (12 papers), semigroups and automata theory (11 papers) and Machine Learning and Algorithms (11 papers). Etsuji Tomita is often cited by papers focused on Algorithms and Data Compression (12 papers), semigroups and automata theory (11 papers) and Machine Learning and Algorithms (11 papers). Etsuji Tomita collaborates with scholars based in Japan, United States and Italy. Etsuji Tomita's co-authors include Haruhisa Takahashi, Akira Tanaka, Tatsuya Akutsu, Asao Fujiyama, Jun‐ichi Suzuki, Takeyuki Tamura, Atsuhiro Takasu, Masaaki Muramatsu, Tsutomu Kawabata and J.B. Brown and has published in prestigious journals such as BMC Bioinformatics, Neural Networks and Theoretical Computer Science.

In The Last Decade

Etsuji Tomita

45 papers receiving 762 citations

Hit Papers

The worst-case time compl... 2006 2026 2012 2019 2006 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Etsuji Tomita Japan 11 397 354 215 162 138 47 818
Konstantin Makarychev United States 18 553 1.4× 349 1.0× 427 2.0× 68 0.4× 172 1.2× 68 1.2k
Luisa Gargano Italy 17 412 1.0× 405 1.1× 547 2.5× 153 0.9× 103 0.7× 88 1.1k
Jacobo Torán Germany 15 721 1.8× 516 1.5× 153 0.7× 35 0.2× 52 0.4× 56 989
Yuri Rabinovich Israel 14 631 1.6× 265 0.7× 325 1.5× 44 0.3× 36 0.3× 38 1.2k
Linda Pagli Italy 14 248 0.6× 147 0.4× 244 1.1× 51 0.3× 43 0.3× 74 613
Alain Bretto France 12 201 0.5× 182 0.5× 108 0.5× 99 0.6× 44 0.3× 47 678
Venkatesh Srinivasan Canada 14 166 0.4× 413 1.2× 192 0.9× 141 0.9× 41 0.3× 77 783
Ravi B. Boppana United States 13 744 1.9× 532 1.5× 216 1.0× 48 0.3× 49 0.4× 26 1.1k
Torben Hagerup Germany 19 627 1.6× 636 1.8× 502 2.3× 29 0.2× 129 0.9× 65 1.3k
Baharan Mirzasoleiman United States 13 217 0.5× 331 0.9× 233 1.1× 186 1.1× 20 0.1× 28 684

Countries citing papers authored by Etsuji Tomita

Since Specialization
Citations

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

Fields of papers citing papers by Etsuji Tomita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Etsuji Tomita

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

All Works

20 of 20 papers shown
1.
Tomita, Etsuji & Alessio Conte. (2020). Another time-complexity analysis for the maximal clique enumeration algorithm CLIQUES. IEICE technical report. Speech. 120(2020). 1–8. 1 indexed citations
2.
3.
Tomita, Etsuji, et al.. (2013). A Simple and Faster Branch-and-Bound Algorithm for Finding a Maximum Clique with Computational Experiments. IEICE Transactions on Information and Systems. E96.D(6). 1286–1298. 13 indexed citations
4.
Tomita, Etsuji, et al.. (2009). Clique-based data mining for related genes in a biomedical database. BMC Bioinformatics. 10(1). 205–205. 18 indexed citations
5.
Tomita, Etsuji, et al.. (2007). A More Efficient Algorithm for Finding a Maximum Clique with an Improved Approximate Coloring.. Parallel and Distributed Processing Techniques and Applications. 719–725. 1 indexed citations
6.
Kobayashi, Satoshi, et al.. (2006). Grammatical Inference: Algorithms and Applications: 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006, Proceedings (Lecture Notes in Computer Science). Springer eBooks. 1 indexed citations
7.
Tomita, Etsuji, Akira Tanaka, & Haruhisa Takahashi. (2004). The Worst-Case Time Complexity for Generating All Maximal Cliques (Extended Abstract). Lecture notes in computer science. 161–170. 2 indexed citations
8.
Tomita, Etsuji, et al.. (2004). Polynomial time learning of simple deterministic languages via queries and a representative sample. Theoretical Computer Science. 329(1-3). 203–221. 1 indexed citations
9.
Akutsu, Tatsuya, et al.. (2004). Protein side-chain packing problem: a maximum edge-weight clique algorithmic approach. 191–200. 7 indexed citations
10.
Tomita, Etsuji, et al.. (2002). An Algorithm for Finding a Maximum Clique with Maximum Edge - Weight and Computational Experiments. IPSJ SIG Notes. 2002(114). 45–48. 6 indexed citations
11.
Akutsu, Tatsuya, et al.. (2002). Point matching under non - uniform distortions and protein side chain packing based on efficient maximum clique algorithms. IPSJ SIG Notes. 2002(36). 21–24. 8 indexed citations
12.
Tomita, Etsuji, et al.. (1998). A Polynomial-Time Algorithm for Checking the Inclusion for Real-Time Deterministic Restricted One-Counter Automata Which Accept by Accept Mode. IEICE Transactions on Information and Systems. 81(1). 1–11. 2 indexed citations
13.
Tomita, Etsuji, et al.. (1995). A Polynomial-Time Algorithm for Checking the Inclusion for Strict Deterministic Restricted One-Counter Automata. IEICE Transactions on Information and Systems. 78(4). 305–313. 2 indexed citations
14.
Tomita, Etsuji, et al.. (1995). A Polynomial-Time Algorithm for Checking the Inclusion for Real-Time Deterministic Restricted One-Counter Automata Which Accept by Final State. IEICE Transactions on Information and Systems. 78(8). 939–950. 4 indexed citations
15.
Tomita, Etsuji, et al.. (1995). The extended equivalence problem for a class of non-real-time deterministic pushdown automata. Acta Informatica. 32(4). 395–413. 1 indexed citations
16.
Tomita, Etsuji, et al.. (1993). A Fast Algorithm for Checking the Inclusion for Very Simple Deterministic Pushdown Automata. IEICE Transactions on Information and Systems. 76(10). 1224–1233. 7 indexed citations
17.
Tomita, Etsuji, et al.. (1993). A Randomized Algorithm for Finding a Near-Maximum Clique and Its Experimental Evaluations. Transactions of the Institute of Electronics, Information and Communication Engineers. 76(2). 46–53. 3 indexed citations
18.
Tomita, Etsuji, Akira Tanaka, & Haruhisa Takahashi. (1989). An Optimal Algorithm for Finding All the Cliques. 1989(98). 91–98. 9 indexed citations
19.
Tomita, Etsuji, et al.. (1985). A weaker sufficient condition for the equivalence of a pair of DPDA's to be decidable. Theoretical Computer Science. 41. 223–230. 3 indexed citations
20.
Tomita, Etsuji. (1984). An extended direct branching algorithm for checking equivalence of deterministic pushdown automata. Theoretical Computer Science. 32(1-2). 87–120. 8 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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