Jinze Bai

17 total papers · 826 total citations
4 papers, 182 citations indexed

About

Jinze Bai is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Jinze Bai has authored 4 papers receiving a total of 182 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 Management Science and Operations Research. Recurrent topics in Jinze Bai's work include Recommender Systems and Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Data Quality and Management (1 paper). Jinze Bai is often cited by papers focused on Recommender Systems and Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Data Quality and Management (1 paper). Jinze Bai collaborates with scholars based in China, United States and Australia. Jinze Bai's co-authors include Xiaofei Liu, Jun Gao, Chang Zhou, Junshuai Song, Jun Gao, Zhao Li, Ji Zhang, Jialin Wang, Ji Zhang and Jialin Wang and has published in prestigious journals such as IEEE Access, IEEE Transactions on Knowledge and Data Engineering and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Jinze Bai

4 papers receiving 173 citations

Author Peers

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

Author						Papers	Cites
Jinze Bai	154	117	50	36	19	4	182
Kun Zhang	197 1.3×	169 1.4×	47 0.9×	30 0.8×	14 0.7×	9	257
将尚渡辺	149 1.0×	97 0.8×	60 1.2×	24 0.7×	46 2.4×	5	238
Yan Li	142 0.9×	130 1.1×	55 1.1×	21 0.6×	9 0.5×	5	205
Cong Quan	221 1.4×	204 1.7×	58 1.2×	31 0.9×	8 0.4×	6	291
Md Mehrab Tanjim	78 0.5×	131 1.1×	22 0.4×	26 0.7×	11 0.6×	8	218
Zhichao Feng	227 1.5×	187 1.6×	53 1.1×	58 1.6×	25 1.3×	6	255
Marcel Genzmehr	198 1.3×	140 1.2×	48 1.0×	39 1.1×	4 0.2×	7	251
Mahsa Ebrahimian	144 0.9×	112 1.0×	25 0.5×	24 0.7×	6 0.3×	7	242
Jinbae Im	175 1.1×	182 1.6×	55 1.1×	63 1.8×	11 0.6×	4	240
Yingqian Min	196 1.3×	161 1.4×	44 0.9×	45 1.3×	25 1.3×	4	216

Countries citing papers authored by Jinze Bai

Since Specialization

Citations

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

Fields of papers citing papers by Jinze Bai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinze Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Jinze Bai. A scholar is included among the top collaborators of Jinze Bai 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 Jinze Bai. Jinze Bai 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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