Cong Quan

12 total papers · 488 total citations
6 papers, 291 citations indexed

About

Cong Quan is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Cong Quan has authored 6 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Information Systems, 3 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Cong Quan's work include Recommender Systems and Techniques (3 papers), Advanced Graph Neural Networks (2 papers) and Topic Modeling (2 papers). Cong Quan is often cited by papers focused on Recommender Systems and Techniques (3 papers), Advanced Graph Neural Networks (2 papers) and Topic Modeling (2 papers). Cong Quan collaborates with scholars based in China and Hong Kong. Cong Quan's co-authors include Chenliang Li, Libing Wu, Xiangyang Luo, Qian Wang, Bolong Zheng, Yuming Deng, Qiegen Liu, Yang Chen, Shanshan Wang and Jinjie Zhou and has published in prestigious journals such as IEEE Transactions on Medical Imaging, ACM Transactions on Information Systems and Investigative Magnetic Resonance Imaging.

In The Last Decade

Cong Quan

6 papers receiving 287 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Cong Quan	221	204	58	31	25	6	291
Milad Ahmadian	163 0.7×	178 0.9×	69 1.2×	29 0.9×	43 1.7×	11	295
Imrana Abdullahi Yari	69 0.3×	241 1.2×	27 0.5×	12 0.4×	32 1.3×	7	319
Mohammad Al-Rubaie	48 0.2×	223 1.1×	46 0.8×	8 0.3×	9 0.4×	5	300
Danyang Liu	192 0.9×	199 1.0×	42 0.7×	22 0.7×	2 0.1×	7	268
Kun Zhang	197 0.9×	169 0.8×	47 0.8×	30 1.0×	3 0.1×	9	257
Lemei Zhang	178 0.8×	199 1.0×	46 0.8×	23 0.7×	2 0.1×	8	254
Bernd Malle	28 0.1×	164 0.8×	39 0.7×	6 0.2×	19 0.8×	4	264
Ruohan Zhan	53 0.2×	45 0.2×	159 2.7×	30 1.0×	25 1.0×	9	241
Negar Maleki	40 0.2×	135 0.7×	33 0.6×	18 0.6×	73 2.9×	9	298
Bruno Trstenjak	102 0.5×	173 0.8×	13 0.2×	9 0.3×	5 0.2×	8	272

Countries citing papers authored by Cong Quan

Since Specialization

Citations

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

Fields of papers citing papers by Cong Quan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Quan

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

All Works

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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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