Dain Kaplan

560 citations
10 papers · 109 indexed · h-index 6
Topics
Topic Modeling (6 papers)Natural Language Processing Techniques (5 papers)Semantic Web and Ontologies (4 papers)
Journals
Language Resources and EvaluationInternational Journal of Information Systems and Social ChangeJournal of Information Processing
Partner nations
JapanUnited StatesTaiwan

In The Last Decade

Dain Kaplan

9 papers receiving 87 citations

Peers

Dain Kaplan
Comparison fields: 5 of 30
  • Artificial Intelligence 90
  • Information Systems 15
  • Molecular Biology 14
  • Political Science and International Relations 6
  • Strategy and Management 6
Replace Salah Aı̈t-Mokhtar with:
Salah Aı̈t-Mokhtar France
Marco Antonio Soares Brazil
Suyang Dai China
Alon Halfon Israel
Brigitte Endres‐Niggemeyer Germany
Alison R. Panisson Brazil
Fernando R. Velázquez–Quesada Netherlands
Bruce Herr United States
Sebastian Kohlmeier United States
Niraj Aswani United Kingdom
Dain Kaplan relative to Salah Aı̈t-Mokhtar France Salah Aı̈t-Mokhtar's profile →
Citations per field
00.5×12×
Salah Aı̈t-Mokhtar · 1×
Citations per year

Countries citing papers authored by Dain Kaplan

Since Specialization
Citations

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

Fields of papers citing papers by Dain Kaplan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dain Kaplan

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 24
2 11
3 0
4 17
5 1
6 12
7
Annotation Process Management Revisited
5
8 2
9 34
10
Adapting International Standard for Asian Language Technologies
3

About Dain Kaplan

Dain Kaplan is a scholar working on Computer Science Applications, Artificial Intelligence and Information Systems and Management, having authored 10 papers that have together received 109 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (90 citations), Management of Technology and Innovation (6 citations) and Statistics, Probability and Uncertainty (6 citations). Dain Kaplan has collaborated with scholars based in Japan, United States and Taiwan. Frequent co-authors include Takenobu Tokunaga, Ryu Iida, Simone Teufel, Neil Rubens, Toshio Okamoto, J. D. Williams, Diarmuid Ó Séaghdha, Shruti Bhargava Choubey, Hėctor Martínez Alonso and Anders Johannsen. Their work appears in journals such as Language Resources and Evaluation, International Journal of Information Systems and Social Change and Journal of Information Processing.

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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