Takumi Maruyama

14 total papers · 4.0k total citations
7 papers, 47 citations indexed

About

Takumi Maruyama is a scholar working on Artificial Intelligence, Computer Networks and Communications and Molecular Biology. According to data from OpenAlex, Takumi Maruyama has authored 7 papers receiving a total of 47 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Molecular Biology. Recurrent topics in Takumi Maruyama's work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Text Readability and Simplification (4 papers). Takumi Maruyama is often cited by papers focused on Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Text Readability and Simplification (4 papers). Takumi Maruyama collaborates with scholars based in Japan and France. Takumi Maruyama's co-authors include Kazuhide Yamamoto, Vincent Couderc, Junko Kano, Masayuki Noguchi, Hideaki Kano, Philippe Leproux, Hiroyuki Miyazaki, Shota Nakamura, Daisuke Motooka and Yuki Matsumoto and has published in prestigious journals such as Language Resources and Evaluation, OSA Continuum and 2022 IEEE International Solid- State Circuits Conference (ISSCC).

In The Last Decade

Takumi Maruyama

6 papers receiving 44 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Takumi Maruyama 21 20 17 8 5 7 47
Yiran Wu 7 0.3× 15 0.8× 13 0.8× 6 42
L. Clissa 18 0.9× 10 0.5× 1 0.1× 1 0.1× 10 2.0× 6 40
Charles Spencer 6 0.3× 18 0.9× 1 0.1× 5 1.0× 5 41
Mehran Soltani 9 0.4× 13 0.7× 7 1.4× 7 32
Ranjan Mondal 2 0.1× 19 0.9× 12 0.7× 9 221
Hagar Hussein 10 0.5× 14 0.7× 7 1.4× 6 34
Kangling He 20 1.0× 36 2.1× 9 1.8× 7 46
Rui Wang 5 0.2× 7 0.3× 1 0.1× 12 2.4× 5 47
Mark S. Keller 9 0.4× 4 0.2× 13 2.6× 6 31
Stefan G. Stark 12 0.6× 5 0.3× 40 8.0× 6 59

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

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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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