Masayuki Takeda
- Hardware and Architecture top 5%
- Network Packet Processing and Optimization 28
- Artificial Intelligence top 5%
- Algorithms and Data Compression 74
- Natural Language Processing Techniques 27
- Machine Learning and Algorithms 6
-
- semigroups and automata theory 33
- Genetics top 10%
-
- DNA and Biological Computing 25
- Genomics and Phylogenetic Studies 5
- Gene expression and cancer classification 4
Masayuki Takeda
84 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Pathology and Forensic Medicine 539
- Hardware and Architecture 163
- Artificial Intelligence 405
- Computational Theory and Mathematics 146
- Genetics 258
Countries citing papers authored by Masayuki Takeda
This map shows the geographic impact of Masayuki Takeda'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 Masayuki Takeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masayuki Takeda more than expected).
Fields of papers citing papers by Masayuki Takeda
This network shows the impact of papers produced by Masayuki Takeda. 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 Masayuki Takeda. The network helps show where Masayuki Takeda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masayuki Takeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2022 | 0 | |
| 3 | 2022 | 0 | |
| 4 | 2021 | 2 | |
| 5 | 2019 | 1 | |
| 6 | Online Rank Aggregation | 2012 | 7 |
| 7 | Online Learning of Maximum p-Norm Margin Classifiers with Bias. | 2008 | 1 |
| 8 | Parameterized Suffix Arrays for Binary Strings. | 2008 | 11 |
| 9 | On-line linear-time construction of word suffix trees | 2006 | 2 |
| 10 | A Fully Compressed Pattern Matching Algorithm for Simple Collage Systems. | 2004 | 2 |
| 11 | 2004 | 0 | |
| 12 | 2003 | 4 | |
| 13 | A Note on Randomized Algorithm for String Matching with Mismatches | 2002 | 4 |
| 14 | Speeding Up String Pattern Matching by Text Compression: The Dawn of a New Era | 2001 | 10 |
| 15 | Construction of the CDAWG for a Trie. | 2001 | 7 |
| 16 | Compressed Pattern Matching for SEQUITUR | 2000 | 1 |
| 17 | 2000 | 2 | |
| 18 | A Boyer-Moore Type Algorithm for Compressed Pattern Matching | 1999 | 1 |
| 19 | Pattern Matching Machine for Text Compressed Using Finite State Model | 1997 | 2 |
| 20 | A Method for Determining Verb of Sentences in Abstracts of Scientific and Technical Literature | 1993 | 2 |
About Masayuki Takeda
Masayuki Takeda is a scholar working on Hardware and Architecture, Artificial Intelligence and Computational Theory and Mathematics, having authored 94 papers that have together received 1.4k indexed citations. Recurring topics across this work include Algorithms and Data Compression (74 papers), semigroups and automata theory (33 papers), Network Packet Processing and Optimization (28 papers), Natural Language Processing Techniques (27 papers), DNA and Biological Computing (25 papers), Machine Learning and Algorithms (6 papers), Genomics and Phylogenetic Studies (5 papers) and Gene expression and cancer classification (4 papers). The work is most often cited by research in Pathology and Forensic Medicine (539 citations), Hardware and Architecture (163 citations) and Artificial Intelligence (405 citations). Masayuki Takeda has collaborated with scholars based in Japan, Germany and Finland. Frequent co-authors include Hiroshi Sakagami, K Konno, Tohru Yamazaki, Shusaku Yoshiki, Chisato Miyaura, Toshio Suda, Ayumi Shinohara, Shunsuke Inenaga, Setsuo Arikawa and Hideo Bannai. Their work appears in journals such as Theoretical Computer Science, Algorithmica, Discrete Applied Mathematics, Theory of Computing Systems 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.