Xifeng Yan

20.6k total citations · 3 hit papers
179 papers, 11.4k citations indexed

About

Xifeng Yan is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Xifeng Yan has authored 179 papers receiving a total of 11.4k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Artificial Intelligence, 70 papers in Information Systems and 48 papers in Computer Networks and Communications. Recurrent topics in Xifeng Yan's work include Data Mining Algorithms and Applications (42 papers), Advanced Graph Neural Networks (38 papers) and Complex Network Analysis Techniques (35 papers). Xifeng Yan is often cited by papers focused on Data Mining Algorithms and Applications (42 papers), Advanced Graph Neural Networks (38 papers) and Complex Network Analysis Techniques (35 papers). Xifeng Yan collaborates with scholars based in United States, China and Singapore. Xifeng Yan's co-authors include Jiawei Han, Jiawei Han, Philip S. Yu, Hong Cheng, Yizhou Sun, Dong Xin, Tianyi Wu, Arijit Khan, Samuel P. Midkiff and Chao Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Software Engineering.

In The Last Decade

Xifeng Yan

174 papers receiving 10.8k 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.

gSpan: graph-based substructure pattern mining

2003 1.3k citations Xifeng Yan, Jiawei Han profile →
PathSim

2011 1.2k citations Jiawei Han, Xifeng Yan et al. Proceedings of the VLDB Endowment profile →
Frequent pattern mining: current status and future directions

2007 869 citations Jiawei Han, Hong Cheng et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xifeng Yan United States	54	5.8k	5.7k	2.8k	2.8k	2.6k	179	11.4k
Mohammed J. Zaki United States	50	6.1k 1.1×	8.0k 1.4×	2.4k 0.8×	3.6k 1.3×	1.2k 0.5×	239	12.6k
Hong Cheng Hong Kong	39	3.3k 0.6×	2.6k 0.4×	1.4k 0.5×	1.4k 0.5×	1.2k 0.5×	145	6.3k
Arthur Asuncion United States	13	13.5k 2.3×	2.7k 0.5×	1.2k 0.4×	1.9k 0.7×	4.7k 1.8×	19	17.4k
Jeffrey Xu Yu Hong Kong	54	5.7k 1.0×	2.9k 0.5×	4.8k 1.7×	4.7k 1.6×	3.0k 1.2×	418	11.8k
Berthier Ribeiro‐Neto Brazil	25	5.1k 0.9×	5.0k 0.9×	2.0k 0.7×	1.8k 0.6×	1.9k 0.7×	68	9.3k
ChengXiang Zhai United States	66	11.4k 2.0×	8.0k 1.4×	1.1k 0.4×	1.5k 0.5×	2.4k 0.9×	386	16.9k
Haixun Wang United States	50	6.2k 1.1×	2.7k 0.5×	3.1k 1.1×	3.1k 1.1×	2.1k 0.8×	231	9.6k
Tao Li United States	45	4.7k 0.8×	2.5k 0.4×	1.6k 0.6×	1.5k 0.5×	2.0k 0.8×	257	8.9k
Aristides Gionis Finland	50	5.5k 0.9×	3.5k 0.6×	2.6k 0.9×	2.8k 1.0×	2.9k 1.1×	200	11.7k
Hanghang Tong United States	47	5.7k 1.0×	2.1k 0.4×	1.9k 0.7×	937 0.3×	2.6k 1.0×	327	10.5k

Countries citing papers authored by Xifeng Yan

Since Specialization

Citations

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

Fields of papers citing papers by Xifeng Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xifeng Yan

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

20 of 20 papers shown

1.

Li, Zekun, Zhiyu Chen, Mike Ross, et al.. (2024). Large Language Models as Zero-shot Dialogue State Tracker through Function Calling. 8688–8704. 1 indexed citations

2.

Yan, Xifeng, et al.. (2024). Financial Forecasting from Textual and Tabular Time Series. 8289–8300.

3.

Li, Zekun, Baolin Peng, Pengcheng He, & Xifeng Yan. (2024). Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection. 557–568. 6 indexed citations

4.

Wang, Hong, et al.. (2023). Limitations of Language Models in Arithmetic and Symbolic Induction. 9285–9298. 15 indexed citations

5.

Ma, Ning, Jiajun Bu, Jun Wen, et al.. (2022). Context-guided entropy minimization for semi-supervised domain adaptation. Neural Networks. 154. 270–282. 18 indexed citations

6.

Li, Zekun, et al.. (2022). Controllable Dialogue Simulation with In-context Learning. 4330–4347. 11 indexed citations

7.

Bu, Jiajun, et al.. (2022). Cross-modal image retrieval with deep mutual information maximization. Neurocomputing. 496. 166–177. 15 indexed citations

8.

Qiu, Nianwei, Tian Li, Xifeng Yan, et al.. (2021). The Interplay between Calcium and Strontium in Chinese Cabbage under Normal and Low Calcium Conditions. HortScience. 56(8). 875–880. 6 indexed citations

9.

Li, Shiyang, Xiaoyong Jin, Yao Xuan, et al.. (2019). Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting. arXiv (Cornell University). 32. 5243–5253. 47 indexed citations

10.

Su, Yu, Huan Sun, Brian M. Sadler, et al.. (2016). On Generating Characteristic-rich Question Sets for QA Evaluation. 562–572. 54 indexed citations

11.

Yang, Shengqi, et al.. (2016). Fast top-k search in knowledge graphs. 990–1001. 35 indexed citations

12.

Sun, Huan, et al.. (2013). Synthetic review spamming and defense. 155–156. 17 indexed citations

13.

Khan, Arijit, et al.. (2011). Neighborhood based fast graph search in large networks. 901–912. 83 indexed citations

14.

Zhu, Feida, Qiang Qu, David Lo, et al.. (2011). Mining top-K large structural patterns in a massive network. Proceedings of the VLDB Endowment. 4(11). 807–818. 49 indexed citations

15.

Chen, Chen, Xifeng Yan, Philip S. Yu, et al.. (2007). Towards graph containment search and indexing. Very Large Data Bases. 926–937. 55 indexed citations

16.

Cheng, Tao, Xifeng Yan, & Kevin Chen–Chuan Chang. (2007). EntityRank: searching entities directly and holistically. Very Large Data Bases. 387–398. 109 indexed citations

17.

Xin, Dong, Jiawei Han, Xifeng Yan, & Hong Cheng. (2005). Mining compressed frequent-pattern sets. Very Large Data Bases. 709–720. 127 indexed citations

18.

Liu, Chao, Xifeng Yan, Fei Long, Jiawei Han, & Samuel P. Midkiff. (2005). SOBER. ACM SIGSOFT Software Engineering Notes. 30(5). 286–295. 89 indexed citations

19.

Yan, Xifeng, et al.. (2003). CloSpan: Mining: Closed Sequential Patterns in Large Datasets. 166–177. 300 indexed citations

20.

Yan, Xifeng & Jiawei Han. (2003). gSpan: graph-based substructure pattern mining. 721–724. 1259 indexed citations breakdown →

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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