Takumi Maruyama

4.0k citations
7 papers · 49 indexed · h-index 4
Topics
Natural Language Processing Techniques (4 papers)Text Readability and Simplification (4 papers)Topic Modeling (4 papers)
Journals
Language Resources and EvaluationOSA Continuum2022 IEEE International Solid- State Circuits Conference (ISSCC)
Partner nations
JapanFrance

In The Last Decade

Takumi Maruyama

6 papers receiving 46 citations

Peers

Takumi Maruyama
Comparison fields: 5 of 27
  • Artificial Intelligence 21
  • Biophysics 21
  • Analytical Chemistry 17
  • Insect Science 8
  • Molecular Biology 5
Replace Leonid Kostrykin with:
Leonid Kostrykin Germany
Mehran Soltani Denmark
Kannappan Palaniappan United States
Sofya Chepushtanova United States
Xudong Wei China
Anfeng He China
Charline Le Lan United Kingdom
Karsten Luebke Germany
Afia Anjum Canada
Takumi Maruyama relative to Leonid Kostrykin Germany Leonid Kostrykin's profile →
Citations per field
00.5×10×17×
Leonid Kostrykin · 1×
Citations per year

Countries citing papers authored by Takumi Maruyama

Since Specialization
Citations

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

Fields of papers citing papers by Takumi Maruyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takumi Maruyama

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

All Works

7 of 7 papers shown
#WorkIndexed citations
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5 24
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Simplified Corpus with Core Vocabulary.
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About Takumi Maruyama

Takumi Maruyama is a scholar working on Biophysics, Hardware and Architecture and Artificial Intelligence, having authored 7 papers that have together received 49 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Text Readability and Simplification (4 papers) and Topic Modeling (4 papers). The work is most often cited by research in Biophysics (21 citations), Analytical Chemistry (17 citations) and Artificial Intelligence (21 citations). Takumi Maruyama has collaborated with scholars based in Japan and France. Frequent co-authors include Kazuhide Yamamoto, Junko Kano, Vincent Couderc, Philippe Leproux, Hideaki Kano, Masayuki Noguchi, Shota Nakamura, Yuki Matsumoto, Hiroyuki Miyazaki and Daisuke Motooka. Their work appears in journals such as Language Resources and Evaluation, OSA Continuum and 2022 IEEE International Solid- State Circuits Conference (ISSCC).

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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