T. Lin

1.7k citations
41 papers · 644 · h-index 10

Impact in

Papers in

T. Lin

37 papers receiving 610 citations

Peers

T. Lin
Comparison fields: 5 of 49
  • Computational Theory and Mathematics 532
  • Information Systems 246
  • Management Science and Operations Research 119
  • Artificial Intelligence 292
  • Signal Processing 78
Replace LV Yue-jin with:
LV Yue-jin China
Xiaoyan Zhang China
Ningxin Xie China
Gangqiang Zhang China
Rajen B. Bhatt India
Zhehuang Huang China
Ewa Orłowska Poland
Yanhong She China
T. Lin relative to LV Yue-jin China LV Yue-jin's profile →
Citations per field
00.5×1.5×
LV Yue-jin · 1×
Citations per year

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-authors

The 25 scholars most cited alongside T. Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with T. Lin Line = papers co-authored together T. Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996285
2 199778
3 200363
4 200528
5 200526
6 200218
7 200412
8 200412
9 200211
10 200510
11 20038
12 20028
13 19988
14
Rough set theory in very large databases
19967
15 19937
16 20046
17 20036
18 20026
19
Inference Secure Multilevel Databases.
19925
20 20085

About T. Lin

T. Lin is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 644 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (24 papers), Data Mining Algorithms and Applications (10 papers), Advanced Algebra and Logic (7 papers), Fuzzy Logic and Control Systems (5 papers), Multi-Criteria Decision Making (4 papers), Semantic Web and Ontologies (4 papers), Data Management and Algorithms (3 papers) and Imbalanced Data Classification Techniques (3 papers). The work is most often cited by research in Computational Theory and Mathematics (532 citations), Information Systems (246 citations), Management Science and Operations Research (119 citations), Artificial Intelligence (292 citations) and Signal Processing (78 citations). T. Lin has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Yiyu Yao, S. K. M. Wong, E. Louie, Shusaku Tsumoto, Churn‐Jung Liau, Xiaohua Hu, Yufeng Yao, Abraham Kandel, James F. Peters and Xiaohua Hu. Their work appears in journals such as Information Sciences, International Journal of Approximate Reasoning, Expert Systems with Applications, Measurement Science and Technology and Intelligent Automation & Soft Computing.

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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