Taketoshi Yoshida

3.7k citations
92 papers · 2.6k indexed · 1 hit paper · h-index 23
Topics
Text and Document Classification Technologies (11 papers)Neonatal Respiratory Health Research (9 papers)Advanced Text Analysis Techniques (7 papers)
Partner nations
JapanChinaUnited States

In The Last Decade

Taketoshi Yoshida

86 papers receiving 2.5k citations

Hit Papers

A comparative study of TF*IDF, LSI and multi-words for te...20102026201520202010100200300400

Peers

Taketoshi Yoshida
Comparison fields: 5 of 181
  • Artificial Intelligence 856
  • Information Systems 553
  • Immunology 474
  • Molecular Biology 343
  • Epidemiology 188
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Ping Luo China
Javed Khan United States
Michel Klein Netherlands
Jun Yan China
Michael Greenberg United States
Jong Kim South Korea
Satwinder Singh India
Mehmet Koyutürk United States
Fusheng Wang United States
Yulan He United Kingdom
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Citations per field
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Countries citing papers authored by Taketoshi Yoshida

Since Specialization
Citations

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

Fields of papers citing papers by Taketoshi Yoshida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taketoshi Yoshida

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
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4 1
5 1
6 7
7 17
8 2
9 17
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11 8
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Augmented Mutual Information for Multi-word Extraction
11
13 6
14 24
15 2
16 86
17
Removing capability for formaldehyde of plant growing in an activated carbon pot
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18 38
19 119
20 10

About Taketoshi Yoshida

Taketoshi Yoshida is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health and Information Systems, having authored 92 papers that have together received 2.6k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (11 papers), Neonatal Respiratory Health Research (9 papers) and Advanced Text Analysis Techniques (7 papers). The work is most often cited by research in Artificial Intelligence (856 citations), Information Systems (553 citations) and Immunology (474 citations). Taketoshi Yoshida has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Xijin Tang, Wen Zhang, Wen Zhang, Andreas Radbruch, Falk Hiepe, Henrik E. Mei, Thomas Dörner, Hirokazu Kanegane, Qing Wang and Bimba F. Hoyer. Their work appears in journals such as Blood, PLoS ONE and PEDIATRICS.

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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