Reina Akama

5 papers and 25 indexed citations i.

About

Reina Akama is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Language and Linguistics. According to data from OpenAlex, Reina Akama has authored 5 papers receiving a total of 25 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Statistical and Nonlinear Physics and 1 paper in Language and Linguistics. Recurrent topics in Reina Akama’s work include Topic Modeling (4 papers), Speech and dialogue systems (4 papers) and Natural Language Processing Techniques (3 papers). Reina Akama is often cited by papers focused on Topic Modeling (4 papers), Speech and dialogue systems (4 papers) and Natural Language Processing Techniques (3 papers). Reina Akama collaborates with scholars based in Japan, United States and Switzerland. Reina Akama's co-authors include Kentaro Inui, Sho Yokoi, Sosuke Kobayashi, Jun Suzuki, Naoya Inoue and Hiroki Ouchi and has published in prestigious journals such as arXiv (Cornell University), International Joint Conference on Natural Language Processing and Journal of Natural Language Processing.

In The Last Decade

Co-authorship network of co-authors of Reina Akama i

Fields of papers citing papers by Reina Akama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Reina Akama

Since Specialization
Citations

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

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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2025