Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Setsuo Tsuruta
Since
Specialization
Citations
This map shows the geographic impact of Setsuo Tsuruta'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 Setsuo Tsuruta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Setsuo Tsuruta more than expected).
This network shows the impact of papers produced by Setsuo Tsuruta. 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 Setsuo Tsuruta. The network helps show where Setsuo Tsuruta may publish in the future.
Co-authorship network of co-authors of Setsuo Tsuruta
This figure shows the co-authorship network connecting the top 25 collaborators of Setsuo Tsuruta.
A scholar is included among the top collaborators of Setsuo Tsuruta 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 Setsuo Tsuruta. Setsuo Tsuruta is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sakurai, Yoshitaka, et al.. (2009). Modeling Academic Education Processes by Dynamic Storyboarding. Educational Technology & Society. 12(2). 307–333.9 indexed citations
9.
Knauf, Rainer, et al.. (2008). A Priori Evaluation & Refinement of Curricula by Data Mining over Storyboards. The Florida AI Research Society. 335–340.1 indexed citations
Sakurai, Yoshitaka, et al.. (2006). Managing Academic Education through Dynamic Storyboarding. Common Library Network (Der Gemeinsame Bibliotheksverbund). 2006(1). 1611–1619.8 indexed citations
12.
Knauf, Rainer, Setsuo Tsuruta, & Avelino J. González. (2005). Towards modeling human expertise: an empirical case study. Common Library Network (Der Gemeinsame Bibliotheksverbund). 232–237.
13.
Knauf, Rainer, Setsuo Tsuruta, & Avelino J. González. (2005). Overcoming Human Weaknesses in Validation of Knowledge-Based Systems.. 254–263.
14.
Knauf, Rainer, Avelino J. González, & Setsuo Tsuruta. (2003). Utilizing Validation Experience for System Validation.. Common Library Network (Der Gemeinsame Bibliotheksverbund). 223–228.3 indexed citations
15.
Tsuruta, Setsuo, et al.. (2002). Knowledge-Based Validation Method for Validating Intelligent Systems. The Florida AI Research Society. 226–230.7 indexed citations
16.
Tsuruta, Setsuo, et al.. (2001). Knowledge-Embedded Multi-Stage Genetic Algorithm for Interactively Optimizing a Large-Scale Distribution Network. The Florida AI Research Society. 166–170.1 indexed citations
17.
Tsuruta, Setsuo, et al.. (2000). Validation Method for Intelligent Systems. The Florida AI Research Society. 361–365.4 indexed citations
18.
Tsuruta, Setsuo, et al.. (1999). Validation of an Elevator Maintenance Engineer Scheduling AI System and its Knowledge Refinement. The Florida AI Research Society. 521–525.3 indexed citations
Tsuruta, Setsuo, et al.. (1986). Intelligent Communication Terminal for Integrating Voice Data and Video Signals.. International Conference on Communications. 1509–1513.5 indexed citations
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.