Guo-Cheng Lan

993 total citations
42 papers, 719 citations indexed

About

Guo-Cheng Lan is a scholar working on Information Systems, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Guo-Cheng Lan has authored 42 papers receiving a total of 719 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Information Systems, 35 papers in Computational Theory and Mathematics and 22 papers in Artificial Intelligence. Recurrent topics in Guo-Cheng Lan's work include Data Mining Algorithms and Applications (42 papers), Rough Sets and Fuzzy Logic (35 papers) and Imbalanced Data Classification Techniques (16 papers). Guo-Cheng Lan is often cited by papers focused on Data Mining Algorithms and Applications (42 papers), Rough Sets and Fuzzy Logic (35 papers) and Imbalanced Data Classification Techniques (16 papers). Guo-Cheng Lan collaborates with scholars based in Taiwan, China and Japan. Guo-Cheng Lan's co-authors include Tzung‐Pei Hong, Vincent S. Tseng, Jerry Chun‐Wei Lin, Shyue-Liang Wang, Wen-Yang Lin, Chun-Hao Chen, Yuh‐Min Chen, Shing‐Tai Pan, Ming‐Chao Chiang and Pei‐Shan Wu and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Applied Soft Computing.

In The Last Decade

Guo-Cheng Lan

41 papers receiving 694 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Guo-Cheng Lan Taiwan	15	663	505	357	284	57	42	719
Gangin Lee South Korea	19	776 1.2×	542 1.1×	564 1.6×	266 0.9×	90 1.6×	29	880
Heungmo Ryang South Korea	14	724 1.1×	539 1.1×	470 1.3×	238 0.8×	56 1.0×	21	778
Bai En Shie Taiwan	6	912 1.4×	696 1.4×	477 1.3×	333 1.2×	71 1.2×	7	944
Tin Truong Vietnam	15	606 0.9×	411 0.8×	375 1.1×	195 0.7×	77 1.4×	36	663
Hua-Fu Li Taiwan	13	511 0.8×	283 0.6×	336 0.9×	287 1.0×	141 2.5×	38	638
Manuel Calimlim United States	6	573 0.9×	404 0.8×	279 0.8×	231 0.8×	116 2.0×	8	652
Karam Gouda Egypt	8	866 1.3×	620 1.2×	498 1.4×	371 1.3×	148 2.6×	20	1.0k
Nicolas Pasquier France	8	740 1.1×	700 1.4×	396 1.1×	359 1.3×	109 1.9×	18	962
Junfeng Qu China	6	470 0.7×	345 0.7×	267 0.7×	158 0.6×	38 0.7×	23	528
Ching-Jui Hsiao Taiwan	4	462 0.7×	339 0.7×	214 0.6×	200 0.7×	88 1.5×	8	543

Countries citing papers authored by Guo-Cheng Lan

Since Specialization

Citations

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

Fields of papers citing papers by Guo-Cheng Lan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guo-Cheng Lan. 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 Guo-Cheng Lan. The network helps show where Guo-Cheng Lan may publish in the future.

Co-authorship network of co-authors of Guo-Cheng Lan

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

All Works

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20 of 20 papers shown

Hong, Tzung‐Pei, et al.. (2017). Mining high utility partial periodic pattern by GPA. 820–824.

Chen, Chun-Hao, et al.. (2016). Mining fuzzy temporal association rules by item lifespans. Applied Soft Computing. 41. 265–274. 33 indexed citations

Lin, Jerry Chun‐Wei, Tzung‐Pei Hong, & Guo-Cheng Lan. (2015). Updating the Sequential Patterns in Dynamic Databases for Customer Sequences Deletion. 網際網路技術學刊. 16(3). 369–377. 1 indexed citations

Lin, Jerry Chun‐Wei, Guo-Cheng Lan, & Tzung‐Pei Hong. (2015). Mining high utility itemsets for transaction deletion in a dynamic database. Intelligent Data Analysis. 19(1). 43–55. 10 indexed citations

Lan, Guo-Cheng, et al.. (2015). Tightening upper bounds for mining weighted frequent itemsets. Intelligent Data Analysis. 19(2). 413–429. 7 indexed citations

Hong, Tzung‐Pei, et al.. (2014). A two-phase approach for mining weighted partial periodic patterns. Engineering Applications of Artificial Intelligence. 30. 225–234. 10 indexed citations

Lan, Guo-Cheng, et al.. (2014). Fast discovery of high fuzzy utility itemsets. 2764–2767. 3 indexed citations

Lin, Jerry Chun‐Wei, Tzung‐Pei Hong, Wen-Yang Lin, & Guo-Cheng Lan. (2014). Efficient updating of sequential patterns with transaction insertion. Intelligent Data Analysis. 18(6). 1013–1026. 7 indexed citations

Hong, Tzung‐Pei, et al.. (2014). An Efficient Pruning and Filtering Strategy to Mine Partial Periodic Patterns from a Sequence of Event Sets. International Journal of Data Warehousing and Mining. 10(2). 18–38. 1 indexed citations

10.

Lin, Jerry Chun‐Wei, et al.. (2014). A GA-Based Approach to Hide Sensitive High Utility Itemsets. The Scientific World JOURNAL. 2014. 1–12. 25 indexed citations

11.

Lin, Jerry Chun‐Wei, et al.. (2014). Efficient updating of discovered high-utility itemsets for transaction deletion in dynamic databases. Advanced Engineering Informatics. 29(1). 16–27. 38 indexed citations

12.

Hong, Tzung‐Pei, et al.. (2013). An Effective Gradual Data-Reduction Strategy for Fuzzy Itemset Mining. International Journal of Fuzzy Systems. 15(2). 170–181. 14 indexed citations

13.

Lan, Guo-Cheng, et al.. (2013). Enhancing the Efficiency in Mining Weighted Frequent Itemsets. 1104–1108. 5 indexed citations

14.

Chen, Chun-Hao, et al.. (2013). Mining high coherent association rules with consideration of support measure. Expert Systems with Applications. 40(16). 6531–6537. 11 indexed citations

15.

Hong, Tzung‐Pei, et al.. (2013). Projection-based partial periodic pattern mining for event sequences. Expert Systems with Applications. 40(10). 4232–4240. 22 indexed citations

16.

Lan, Guo-Cheng, et al.. (2012). Disease Risk Prediction by Mining Personalized Health Trend Patterns: A Case Study on Diabetes. 27–32. 7 indexed citations

17.

Lan, Guo-Cheng, et al.. (2011). A fuzzy approach for mining general temporal association rules in a publication database. 3214. 611–615. 6 indexed citations

18.

Lan, Guo-Cheng, Tzung‐Pei Hong, & Vincent S. Tseng. (2010). Projection-Based Utility Mining with an Efficient Indexing Mechanism. 4. 137–141. 1 indexed citations

19.

Lan, Guo-Cheng, et al.. (2009). A Framework for Personalized Health Trend Analysis. 77. 405–409. 1 indexed citations

20.

Lan, Guo-Cheng, et al.. (2007). A Decomposition Approach for Mining Frequent Itemsets. 605–608. 2 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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