T. Lin

2.0k total citations
42 papers, 650 citations indexed

About

T. Lin is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems. According to data from OpenAlex, T. Lin has authored 42 papers receiving a total of 650 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computational Theory and Mathematics, 25 papers in Artificial Intelligence and 11 papers in Information Systems. Recurrent topics in T. Lin's work include Rough Sets and Fuzzy Logic (25 papers), Data Mining Algorithms and Applications (10 papers) and Advanced Algebra and Logic (7 papers). T. Lin is often cited by papers focused on Rough Sets and Fuzzy Logic (25 papers), Data Mining Algorithms and Applications (10 papers) and Advanced Algebra and Logic (7 papers). T. Lin collaborates with scholars based in United States, China and Canada. T. Lin's co-authors include Yiyu Yao, S. K. M. Wong, E. Louie, Xiaohua Hu, Churn‐Jung Liau, Shusaku Tsumoto, Yufeng Yao, Abraham Kandel, Jianchao Han and W. C. Lindsey and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Measurement Science and Technology.

In The Last Decade

T. Lin

37 papers receiving 616 citations

Peers

T. Lin

CTM

AI

IS

MSOR

SP

Xiaoyan Zhang China

Ningxin Xie China

Gangqiang Zhang China

Nele Verbiest Belgium

LV Yue-jin China

Suyun Zhao China

Rajen B. Bhatt India

Yuhua Qian China

Anna Maria Radzikowska Poland

Raúl Orduna-Urrutia Spain

Xiaoyan Zhang China

T. Lin

617 ×1.2

CTM

312 ×1.1

AI

251 ×1.0

IS

241 ×2.0

MSOR

65 ×0.8

SP

Citations per year, relative to T. Lin T. Lin (= 1×) peers Xiaoyan Zhang

Countries citing papers authored by T. Lin

Since Specialization

Citations

This map shows the geographic impact of T. Lin'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 T. Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Lin more than expected).

Fields of papers citing papers by T. Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Lin

This figure shows the co-authorship network connecting the top 25 collaborators of T. Lin. A scholar is included among the top collaborators of T. Lin 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 T. Lin. T. Lin 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.

Song, Liuyang, et al.. (2025). A generalization enhanced spatial-time-global competitive network for remaining useful life prediction. Measurement Science and Technology. 36(6). 66106–66106. 1 indexed citations

2.

Huang, Guoheng, Xiaochen Yuan, Guo Zhong, et al.. (2024). The Structure-sharing Hypergraph Reasoning Attention Module for CNNs. Expert Systems with Applications. 259. 125240–125240.

3.

Lin, T., et al.. (2024). A Novel Prompt Tuning for Graph Transformers: Tailoring Prompts to Graph Topologies. 3116–3127. 3 indexed citations

4.

Lin, T., et al.. (2024). Beyond Direct Relationships: Exploring Multi-Order Label Pair Dependencies for Knowledge Distillation. 8527–8535.

5.

Lin, T., et al.. (2023). Graph Quaternion-Valued Attention Networks for Node Classification. 673–677.

6.

Lin, T., et al.. (2023). A Dark Transformation-Equivariant Algorithm for Dark Object Detection. 731–735. 1 indexed citations

7.

Lin, T. & Shusaku Tsumoto. (2008). Qualitative fuzzy sets and granularity. 435–440. 3 indexed citations

8.

Lin, T., et al.. (2008). Granular computing on covering from the aspects of knowledge theory. 33. 1–5. 5 indexed citations

9.

Lin, T.. (2005). Introduction to special issues on data mining and granular computing. International Journal of Approximate Reasoning. 40(1-2). 1–2. 26 indexed citations

10.

Liau, Churn‐Jung & T. Lin. (2005). Reasoning about relational granulation in modal logics. 8. 530–534 Vol. 2. 10 indexed citations

11.

Lin, T. & I‐Jen Chiang. (2005). Semantic based clustering of Web documents. 26. 189–192 Vol. 1. 1 indexed citations

12.

Kandel, Abraham, et al.. (2004). Computational Web Intelligence. 12 indexed citations

13.

Lin, T.. (2002). Sets with partial memberships: a rough set view of fuzzy sets. 1. 785–790. 8 indexed citations

14.

Lin, T.. (2002). A set theory for soft computing: a unified view of fuzzy sets via neighborboods. Proceedings of IEEE 5th International Fuzzy Systems. 2. 1140–1146. 18 indexed citations

15.

Lin, T. & E. Louie. (2002). Modeling the real world for data mining: granular computing approach. 5. 3044–3049. 11 indexed citations

16.

Lin, T.. (1996). Rough set theory in very large databases. 7 indexed citations

17.

Yao, Yiyu & T. Lin. (1996). Generalization of Rough Sets using Modal Logics. Intelligent Automation & Soft Computing. 2(2). 103–119. 285 indexed citations

18.

Lin, T., Zdzisław Pawlak, Jerzy W. Grzymala‐Busse, et al.. (1995). Workshop on rough sets and database mining (panel). 282–282. 3 indexed citations

19.

Lin, T.. (1994). Anomaly detection. 2 indexed citations

20.

Lin, T.. (1992). Inference Secure Multilevel Databases.. 317–332. 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.

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