Young Ae Kim

763 total citations
10 papers, 519 citations indexed

About

Young Ae Kim is a scholar working on Information Systems, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Young Ae Kim has authored 10 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Information Systems, 6 papers in Artificial Intelligence and 4 papers in Sociology and Political Science. Recurrent topics in Young Ae Kim's work include Recommender Systems and Techniques (4 papers), Privacy-Preserving Technologies in Data (3 papers) and Access Control and Trust (3 papers). Young Ae Kim is often cited by papers focused on Recommender Systems and Techniques (4 papers), Privacy-Preserving Technologies in Data (3 papers) and Access Control and Trust (3 papers). Young Ae Kim collaborates with scholars based in South Korea, United States and Singapore. Young Ae Kim's co-authors include Jaideep Srivastava, Muhammad Aurangzeb Ahmad, Aixin Sun, Minh-Tam Le, Ee‐Peng Lim, Hady W. Lauw, Hee Seok Song and Soung Hie Kim and has published in prestigious journals such as Expert Systems with Applications, Knowledge-Based Systems and Expert Systems.

In The Last Decade

Young Ae Kim

9 papers receiving 475 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Young Ae Kim South Korea	6	317	151	129	122	95	10	519
Vasudeva Akula United States	10	332 1.0×	183 1.2×	88 0.7×	72 0.6×	146 1.5×	17	634
Ching‐man Au Yeung United Kingdom	12	287 0.9×	306 2.0×	243 1.9×	79 0.6×	87 0.9×	27	700
Hsuanwei Michelle Chen United States	7	197 0.6×	45 0.3×	73 0.6×	106 0.9×	58 0.6×	16	399
Dirk Thorleuchter Germany	16	129 0.4×	233 1.5×	174 1.3×	64 0.5×	100 1.1×	28	640
Rajhans Mishra India	9	127 0.4×	85 0.6×	130 1.0×	93 0.8×	78 0.8×	25	415
Edna Reid United States	12	261 0.8×	139 0.9×	183 1.4×	68 0.6×	21 0.2×	23	584
Gene Moo Lee United States	10	186 0.6×	102 0.7×	63 0.5×	32 0.3×	103 1.1×	34	437
Noor Farizah Ibrahim Malaysia	7	180 0.6×	135 0.9×	56 0.4×	49 0.4×	79 0.8×	26	356
Aaron M. French United States	14	224 0.7×	69 0.5×	130 1.0×	117 1.0×	72 0.8×	47	509
Taeho Hong South Korea	9	202 0.6×	200 1.3×	61 0.5×	80 0.7×	110 1.2×	27	499

Countries citing papers authored by Young Ae Kim

Since Specialization

Citations

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

Fields of papers citing papers by Young Ae Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young Ae Kim. 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 Young Ae Kim. The network helps show where Young Ae Kim may publish in the future.

Co-authorship network of co-authors of Young Ae Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Young Ae Kim. A scholar is included among the top collaborators of Young Ae Kim 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 Young Ae Kim. Young Ae Kim 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:

10 of 10 papers shown

1.

Kim, Young Ae, et al.. (2022). Exploring Foreign Language Students’ Perceptions of the Guided Use of Machine Translation (GUMT) Model for Korean Writing. L2 Journal. 14(1). 5 indexed citations

2.

Song, Hee Seok & Young Ae Kim. (2020). A dog food recommendation system based on nutrient suitability. Expert Systems. 38(2). 1 indexed citations

3.

Kim, Young Ae. (2017). Trust Relationship Recommendation with Matrix Factorization. The Journal of Korean Institute of Information Technology. 15(10). 17–25.

4.

Kim, Young Ae. (2015). An enhanced trust propagation approach with expertise and homophily-based trust networks. Knowledge-Based Systems. 82. 20–28. 28 indexed citations

5.

Kim, Young Ae, et al.. (2014). Teachers and Students' Recognition about Learning with a Humanoid Robot in Elementary School. The Journal of Korea Robotics Society. 9(3). 185–195. 5 indexed citations

6.

Kim, Young Ae & Muhammad Aurangzeb Ahmad. (2012). Trust, distrust and lack of confidence of users in online social media-sharing communities. Knowledge-Based Systems. 37. 438–450. 75 indexed citations

7.

Song, Hee Seok, et al.. (2009). A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection. Expert Systems with Applications. 36(9). 11595–11604. 36 indexed citations

8.

Lim, Ee‐Peng, Hady W. Lauw, Minh-Tam Le, et al.. (2008). Predicting trusts among users of online communities. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 310–319. 121 indexed citations

9.

Kim, Young Ae & Jaideep Srivastava. (2007). Impact of social influence in e-commerce decision making. 293–302. 240 indexed citations

10.

Kim, Young Ae, Hee Seok Song, & Soung Hie Kim. (2005). Strategies for preventing defection based on the mean time to defection and their implementations on a self-organizing map. Expert Systems. 22(5). 265–278. 8 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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