Tetsuya Murai

747 total citations
62 papers, 305 citations indexed

About

Tetsuya Murai is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems. According to data from OpenAlex, Tetsuya Murai has authored 62 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Computational Theory and Mathematics, 42 papers in Artificial Intelligence and 20 papers in Information Systems. Recurrent topics in Tetsuya Murai's work include Rough Sets and Fuzzy Logic (44 papers), Data Mining Algorithms and Applications (18 papers) and Semantic Web and Ontologies (18 papers). Tetsuya Murai is often cited by papers focused on Rough Sets and Fuzzy Logic (44 papers), Data Mining Algorithms and Applications (18 papers) and Semantic Web and Ontologies (18 papers). Tetsuya Murai collaborates with scholars based in Japan, China and Italy. Tetsuya Murai's co-authors include Yasuo Kudo, Hong-Bin Yan, Yoshiteru Nakamori, Van‐Nam Huynh, Zhipeng Zhang, Seiki Akama, Masaru Shimbo, Germano Resconi, Masaaki Miyakoshi and Michinori Nakata and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Fuzzy Sets and Systems.

In The Last Decade

Tetsuya Murai

51 papers receiving 280 citations

Peers

Tetsuya Murai

AI

CTM

IS

MSOR

SP

Maria Rifqi France

Simon Miller United Kingdom

Dmitry I. Belov Netherlands

Andreas Speck Germany

Matthias Nickles Germany

Salma Jamoussi Tunisia

Shweta Yadav India

Kevin Regan Canada

H. Briand France

Mostafa Aref Egypt

Maria Rifqi France

Tetsuya Murai

207 ×1.7

AI

99 ×0.9

CTM

42 ×0.4

IS

120 ×1.6

MSOR

14 ×0.3

SP

Citations per year, relative to Tetsuya Murai Tetsuya Murai (= 1×) peers Maria Rifqi

Countries citing papers authored by Tetsuya Murai

Since Specialization

Citations

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

Fields of papers citing papers by Tetsuya Murai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tetsuya Murai

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Akama, Seiki, et al.. (2023). Annotated Logic with Rough Double Stone Algebraic Interpretation. 1–6.

2.

Akama, Seiki, et al.. (2020). Rough Set Logic for Kleene's Three-valued Logic. 11. 1–5. 2 indexed citations

3.

Zhang, Zhipeng, et al.. (2019). Addressing Complete New Item Cold-Start Recommendation: A Niche Item-Based Collaborative Filtering via Interrelationship Mining. Applied Sciences. 9(9). 1894–1894. 10 indexed citations

4.

Zhang, Zhipeng, et al.. (2019). Enhancing Recommendation Accuracy of Item-Based Collaborative Filtering via Item-Variance Weighting. Applied Sciences. 9(9). 1928–1928. 17 indexed citations

5.

Akama, Seiki, et al.. (2019). Topics in Rough Set Theory: Current Applications to Granular Computing. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations

6.

Akama, Seiki, Tetsuya Murai, & Yasuo Kudo. (2017). Reasoning with Rough Sets. Intelligent systems reference library. 3 indexed citations

7.

Murai, Tetsuya, et al.. (2014). Crisp and Fuzzy Granular Hierarchical Structures Generated from a Free Monoid. Journal of Advanced Computational Intelligence and Intelligent Informatics. 18(6). 929–936. 5 indexed citations

8.

Kudo, Yasuo & Tetsuya Murai. (2013). A Parallel Computation Method for Heuristic Attribute Reduction Using Reduced Decision Tables. Journal of Advanced Computational Intelligence and Intelligent Informatics. 17(3). 371–376.

9.

Kudo, Mineichi, et al.. (2012). Weighted naïve Bayes classifier on categorical features. 865–870. 3 indexed citations

10.

Kudo, Yasuo & Tetsuya Murai. (2011). Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes. Journal of Advanced Computational Intelligence and Intelligent Informatics. 15(1). 102–109. 3 indexed citations

11.

Kudo, Yasuo, Tetsuya Murai, & Seiki Akama. (2009). A granularity-based framework of deduction, induction, and abduction. International Journal of Approximate Reasoning. 50(8). 1215–1226. 10 indexed citations

12.

Kudo, Yasuo & Tetsuya Murai. (2009). A Modal Characterization of Visibility and Focus in Granular Reasoning. Journal of Advanced Computational Intelligence and Intelligent Informatics. 13(3). 297–303. 1 indexed citations

13.

Kudo, Yasuo & Tetsuya Murai. (2008). A Modal Characterization of Granular Reasoning Based on Scott - Montague Models. 2008. 991–995. 1 indexed citations

14.

Huynh, Van‐Nam, Yoshiteru Nakamori, & Tetsuya Murai. (2007). An Algebraic Foundation for Linguistic Reasoning. Fundamenta Informaticae. 78(2). 271–294.

15.

Miyamoto, Sadaaki, Tetsuya Murai, & Yasuo Kudo. (2006). A Family of Polymodal Systems and its Application to Generalized Possibility Measures and Multi-Rough Sets. Journal of Advanced Computational Intelligence and Intelligent Informatics. 10(5). 625–632.

16.

Kudo, Yasuo & Tetsuya Murai. (2006). A Theoretical Formulation of Object-Oriented Rough Set Models. Journal of Advanced Computational Intelligence and Intelligent Informatics. 10(5). 612–620. 2 indexed citations

17.

Kudo, Mineichi, et al.. (2006). Reduction of Attribute Values for Kansei Representation. Journal of Advanced Computational Intelligence and Intelligent Informatics. 10(5). 666–672. 1 indexed citations

18.

Murai, Tetsuya, et al.. (1997). A Revised Method for Generating Fuzzy Subsets from Tolerance Relations.. International Conference on Neural Information Processing. 543–546.

19.

Murai, Tetsuya, et al.. (1997). An Application of a Way of Generating Fuzzy k-Partitions to Fuzzy Clustering.. International Conference on Neural Information Processing. 1267–1270.

20.

Murai, Tetsuya & Satoru Fukami. (1995). Modal Logic (1). Journal of Japan Society for Fuzzy Theory and Systems. 7(1). 3–18. 1 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.

Explore authors with similar magnitude of impact