Changsung Kang

406 total citations
15 papers, 235 citations indexed

About

Changsung Kang is a scholar working on Information Systems, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Changsung Kang has authored 15 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Information Systems, 10 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Changsung Kang's work include Web Data Mining and Analysis (10 papers), Information Retrieval and Search Behavior (8 papers) and Text and Document Classification Technologies (5 papers). Changsung Kang is often cited by papers focused on Web Data Mining and Analysis (10 papers), Information Retrieval and Search Behavior (8 papers) and Text and Document Classification Technologies (5 papers). Changsung Kang collaborates with scholars based in United States, Canada and United Kingdom. Changsung Kang's co-authors include Yi Chang, Dawei Yin, Jiliang Tang, Hua Ouyang, Yuening Hu, Jin Tian, Dawei Yin, Jianhui Chen, Chikashi Nobata and Hongbo Deng and has published in prestigious journals such as Neurocomputing, IEEE Transactions on Knowledge and Data Engineering and Journal of Machine Learning Research.

In The Last Decade

Changsung Kang

14 papers receiving 216 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Changsung Kang United States 9 170 125 45 28 26 15 235
Damir Vandić Netherlands 9 154 0.9× 131 1.0× 24 0.5× 27 1.0× 40 1.5× 26 220
Victor E. Lee United States 6 98 0.6× 106 0.8× 46 1.0× 15 0.5× 19 0.7× 8 188
Bangzuo Zhang China 9 198 1.2× 164 1.3× 49 1.1× 15 0.5× 16 0.6× 27 287
Srinivasan H. Sengamedu United States 10 189 1.1× 140 1.1× 48 1.1× 25 0.9× 66 2.5× 22 293
Jessica Rosati Italy 6 120 0.7× 123 1.0× 27 0.6× 13 0.5× 56 2.2× 13 216
Hyunsouk Cho South Korea 7 201 1.2× 189 1.5× 61 1.4× 24 0.9× 73 2.8× 13 284
Jiankai Sun United States 9 149 0.9× 175 1.4× 33 0.7× 15 0.5× 46 1.8× 12 250
Gerald Kowalski United States 4 172 1.0× 131 1.0× 54 1.2× 47 1.7× 13 0.5× 5 275
Cheng Xiang Zhai United States 8 241 1.4× 298 2.4× 105 2.3× 54 1.9× 28 1.1× 15 431

Countries citing papers authored by Changsung Kang

Since Specialization
Citations

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

Fields of papers citing papers by Changsung Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changsung Kang

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

All Works

15 of 15 papers shown
1.
2.
Hu, Yuening, Changsung Kang, Jiliang Tang, Dawei Yin, & Yi Chang. (2017). Large-Scale Location Prediction for Web Pages. IEEE Transactions on Knowledge and Data Engineering. 29(9). 1902–1915. 5 indexed citations
3.
Yin, Dawei, Yuening Hu, Jiliang Tang, et al.. (2016). Ranking Relevance in Yahoo Search. 323–332. 77 indexed citations
4.
Jiang, Shan, Yuening Hu, Changsung Kang, et al.. (2016). Learning Query and Document Relevance from a Web-scale Click Graph. 185–194. 34 indexed citations
5.
Tang, Jiliang, et al.. (2016). Learning to Rewrite Queries. 1443–1452. 39 indexed citations
6.
Kang, Changsung, et al.. (2015). Learning to rank related entities in Web search. Neurocomputing. 166. 309–318. 11 indexed citations
7.
Wang, Jingjing, Changsung Kang, Yi Chang, & Jiawei Han. (2014). A hierarchical Dirichlet model for taxonomy expansion for search engines. 961–970. 10 indexed citations
8.
Kang, Changsung, Xuanhui Wang, Yi Chang, & Belle L. Tseng. (2012). Learning to rank with multi-aspect relevance for vertical search. 453–462. 18 indexed citations
9.
Kang, Changsung & Jin Tian. (2012). Polynomial Constraints in Causal Bayesian Networks. arXiv (Cornell University). 200–208. 2 indexed citations
10.
Kang, Changsung, et al.. (2012). Predicting primary categories of business listings for local search. 2591–2594. 1 indexed citations
11.
Kang, Changsung, Xuanhui Wang, Chen Jiang, et al.. (2011). Learning to re-rank web search results with multiple pairwise features. 735–744. 5 indexed citations
12.
Kang, Changsung, Srinivas Vadrevu, Ruiqiang Zhang, et al.. (2011). Ranking related entities for web search queries. 67–68. 8 indexed citations
13.
Kang, Changsung & Jin Tian. (2009). Markov Properties for Linear Causal Models with Correlated Errors. Journal of Machine Learning Research. 10(2). 41–70. 10 indexed citations
14.
Kang, Changsung & Bill Shipley. (2009). A Correction Note on “A New Inferential Test for Path Models Based on Directed Acyclic Graphs”. Structural Equation Modeling A Multidisciplinary Journal. 16(3). 537–538. 4 indexed citations
15.
Kang, Changsung & Jin Tian. (2006). A Hybrid Generative/Discriminative Bayesian Classifier.. The Florida AI Research Society. 562–567. 11 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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