Shih-Wen Ke

921 total citations · 2 hit papers
11 papers, 625 citations indexed

About

Shih-Wen Ke is a scholar working on Artificial Intelligence, Information Systems and Health Information Management. According to data from OpenAlex, Shih-Wen Ke has authored 11 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Information Systems and 2 papers in Health Information Management. Recurrent topics in Shih-Wen Ke's work include Imbalanced Data Classification Techniques (3 papers), Machine Learning and Data Classification (3 papers) and Data Mining Algorithms and Applications (3 papers). Shih-Wen Ke is often cited by papers focused on Imbalanced Data Classification Techniques (3 papers), Machine Learning and Data Classification (3 papers) and Data Mining Algorithms and Applications (3 papers). Shih-Wen Ke collaborates with scholars based in Taiwan and United Kingdom. Shih-Wen Ke's co-authors include Chih‐Fong Tsai, Min‐Wei Huang, Li-Yu Hu, Wei‐Chao Lin, Ya‐Han Hu, Ming‐Yi Lin and Kenneth McGarry and has published in prestigious journals such as PLoS ONE, SpringerPlus and Online Information Review.

In The Last Decade

Shih-Wen Ke

11 papers receiving 609 citations

Hit Papers

align trajectories

What are hit papers?

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.

The distance function effect on k-nearest neighbor classification for medical datasets

2016 298 citations Li-Yu Hu, Min‐Wei Huang et al. SpringerPlus profile →
SVM and SVM Ensembles in Breast Cancer Prediction

2017 236 citations Min‐Wei Huang, Wei‐Chao Lin et al. PLoS ONE profile →

Peers

Shih-Wen Ke

AI

MB

HIM

CVPR

RNMI

Miriam Seoane Santos Portugal

Andrea Bommert Germany

Tze-Yun Leong Singapore

Ali Yaşar Türkiye

George Obaido South Africa

Indro Spinelli Italy

Barbara Pes Italy

Hanaa Salem Egypt

Jong Yun Lee South Korea

Diaa Salama AbdElminaam Egypt

Miriam Seoane Santos Portugal

Shih-Wen Ke

479 ×2.0

AI

72 ×0.6

MB

110 ×1.4

HIM

68 ×1.0

CVPR

86 ×1.3

RNMI

Citations per year, relative to Shih-Wen Ke Shih-Wen Ke (= 1×) peers Miriam Seoane Santos

Countries citing papers authored by Shih-Wen Ke

Since Specialization

Citations

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

Fields of papers citing papers by Shih-Wen Ke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih-Wen Ke. 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 Shih-Wen Ke. The network helps show where Shih-Wen Ke may publish in the future.

Co-authorship network of co-authors of Shih-Wen Ke

This figure shows the co-authorship network connecting the top 25 collaborators of Shih-Wen Ke. A scholar is included among the top collaborators of Shih-Wen Ke 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 Shih-Wen Ke. Shih-Wen Ke 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:

11 of 11 papers shown

1.

Huang, Min‐Wei, et al.. (2017). SVM and SVM Ensembles in Breast Cancer Prediction. PLoS ONE. 12(1). e0161501–e0161501. 236 indexed citations breakdown →

2.

Ke, Shih-Wen, et al.. (2017). When Should We Ignore Examples with Missing Values?. International Journal of Data Warehousing and Mining. 13(4). 53–63. 4 indexed citations

3.

Lin, Wei‐Chao, Shih-Wen Ke, & Chih‐Fong Tsai. (2017). Top 10 data mining techniques in business applications: a brief survey. Kybernetes. 46(7). 1158–1170. 24 indexed citations

4.

Ke, Shih-Wen, Wei‐Chao Lin, & Chih‐Fong Tsai. (2016). Research performance of AACSB accredited institutions in Taiwan: before versus after accreditation. SpringerPlus. 5(1). 1285–1285. 21 indexed citations

5.

Hu, Li-Yu, Min‐Wei Huang, Shih-Wen Ke, & Chih‐Fong Tsai. (2016). The distance function effect on k-nearest neighbor classification for medical datasets. SpringerPlus. 5(1). 1304–1304. 298 indexed citations breakdown →

6.

Ke, Shih-Wen, et al.. (2016). SAFQuery: a simple and flexible advanced Web search interface. The Electronic Library. 34(1). 155–168. 1 indexed citations

7.

Hu, Ya‐Han, et al.. (2016). Research impact of general and funded papers. Online Information Review. 40(4). 472–480. 5 indexed citations

8.

Hu, Ya‐Han, et al.. (2015). An efficient data preprocessing approach for large scale medical data mining. Technology and Health Care. 23(2). 153–160. 15 indexed citations

9.

Tsai, Chih‐Fong, Shih-Wen Ke, Kenneth McGarry, & Ming‐Yi Lin. (2015). LocalContent: a personal scientific document retrieval system. The Electronic Library. 33(3). 373–385. 2 indexed citations

10.

Lin, Wei‐Chao, Chih‐Fong Tsai, & Shih-Wen Ke. (2014). Dimensionality and data reduction in telecom churn prediction. Kybernetes. 43(5). 737–749. 10 indexed citations

11.

Tsai, Chih‐Fong, Ya‐Han Hu, & Shih-Wen Ke. (2014). A Borda count approach to combine subjective and objective based MIS journal rankings. Online Information Review. 38(4). 469–483. 9 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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