Hiroki Arimura
Impact in
- Computational Theory and Mathematics top 0.5%
- Rough Sets and Fuzzy Logic
- semigroups and automata theory
- Information Systems top 0.5%
- Data Mining Algorithms and Applications
Papers in
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- Algorithms and Data Compression 72
- Machine Learning and Algorithms 27
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- semigroups and automata theory 23
- Rough Sets and Fuzzy Logic 19
- Co-authors
- Takeaki Uno (27 shared papers)Setsuo Arikawa (21 shared papers)Tatsuya Asai (7 shared papers)Masashi Kiyomi (2 shared papers)Shinji Kawasoe (5 shared papers)Hiroshi Sakamoto (11 shared papers)Kenji Abe (3 shared papers)Toru Kasai (2 shared papers)
In The Last Decade
Hiroki Arimura
125 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 99
- Computational Theory and Mathematics 1.0k
- Information Systems 1.3k
- Signal Processing 642
- Artificial Intelligence 1.5k
- Hardware and Architecture 184
Countries citing papers authored by Hiroki Arimura
This map shows the geographic impact of Hiroki Arimura'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 Hiroki Arimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroki Arimura more than expected).
Fields of papers citing papers by Hiroki Arimura
This network shows the impact of papers produced by Hiroki Arimura. 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 Hiroki Arimura. The network helps show where Hiroki Arimura may publish in the future.
Co-authors
The 25 scholars most cited alongside Hiroki Arimura, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 133 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 321 | |
| 2 | 2002 | 284 | |
| 3 | LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets | 2004 | 257 |
| 4 | 2005 | 174 | |
| 5 | 2004 | 160 | |
| 6 | 2003 | 126 | |
| 7 | LCM: An Efficient Algorithm for Enumerating Frequent Closed Item Sets. | 2003 | 110 |
| 8 | 2002 | 94 | |
| 9 | 2020 | 77 | |
| 10 | 1994 | 45 | |
| 11 | 1997 | 41 | |
| 12 | 2003 | 40 | |
| 13 | 2000 | 31 | |
| 14 | 2000 | 30 | |
| 15 | 1997 | 29 | |
| 16 | 2000 | 27 | |
| 17 | 2008 | 27 | |
| 18 | 2009 | 27 | |
| 19 | Efficient Substructure Discovery from Large Semi-Structured Data | 2001 | 26 |
| 20 | 2001 | 25 |
About Hiroki Arimura
Hiroki Arimura is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Hardware and Architecture and Signal Processing, having authored 133 papers that have together received 2.6k indexed citations. Recurring topics across this work include Algorithms and Data Compression (72 papers), Data Mining Algorithms and Applications (45 papers), Machine Learning and Algorithms (27 papers), semigroups and automata theory (23 papers), Data Management and Algorithms (20 papers), Rough Sets and Fuzzy Logic (19 papers), Network Packet Processing and Optimization (18 papers) and Advanced Database Systems and Queries (17 papers). The work is most often cited by research in Computational Theory and Mathematics (1.0k citations), Information Systems (1.3k citations), Signal Processing (642 citations), Artificial Intelligence (1.5k citations) and Hardware and Architecture (184 citations). Hiroki Arimura has collaborated with scholars based in Japan, Poland and Singapore. Frequent co-authors include Takeaki Uno, Setsuo Arikawa, Tatsuya Asai, Masashi Kiyomi, Shinji Kawasoe, Hiroshi Sakamoto, Kenji Abe, Toru Kasai, Gun-Ho Lee and Kunsoo Park. Their work appears in journals such as Lecture notes in computer science, Theoretical Computer Science, Discrete Applied Mathematics, Algorithmica and Proceedings Genome Informatics Workshop/Genome informatics.
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.