Dongyan Zhao

10.2k total citations · 1 hit paper
230 papers, 4.6k citations indexed

About

Dongyan Zhao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Dongyan Zhao has authored 230 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 188 papers in Artificial Intelligence, 61 papers in Computer Vision and Pattern Recognition and 40 papers in Information Systems. Recurrent topics in Dongyan Zhao's work include Topic Modeling (138 papers), Natural Language Processing Techniques (112 papers) and Speech and dialogue systems (39 papers). Dongyan Zhao is often cited by papers focused on Topic Modeling (138 papers), Natural Language Processing Techniques (112 papers) and Speech and dialogue systems (39 papers). Dongyan Zhao collaborates with scholars based in China, United States and Hong Kong. Dongyan Zhao's co-authors include Rui Yan, Yansong Feng, Lei Zou, Chongyang Tao, Feifan Fan, Lei Chen, Nanyun Peng, Shen Gao, Jeffrey Xu Yu and M. TAMER ÖZSU and has published in prestigious journals such as SHILAP Revista de lepidopterología, Frontiers in Plant Science and BMC Bioinformatics.

In The Last Decade

Dongyan Zhao

212 papers receiving 4.4k citations

Hit Papers

align trajectories sort by overperformance

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.

Multi-grained Attention Network for Aspect-Level Sentiment Classification

2018 346 citations Feifan Fan, Yansong Feng et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dongyan Zhao China	33	4.0k	1.2k	646	362	353	230	4.6k
Xipeng Qiu China	37	5.1k 1.3×	1.1k 1.0×	803 1.2×	331 0.9×	150 0.4×	194	6.1k
Yue Zhang China	43	5.7k 1.4×	938 0.8×	721 1.1×	171 0.5×	145 0.4×	220	6.7k
Xuanjing Huang China	41	5.6k 1.4×	1.3k 1.1×	1.1k 1.7×	266 0.7×	164 0.5×	233	6.7k
Ting Liu China	31	4.8k 1.2×	429 0.4×	1.6k 2.5×	418 1.2×	311 0.9×	127	5.8k
Ramesh Nallapati United States	24	3.6k 0.9×	657 0.6×	938 1.5×	214 0.6×	219 0.6×	63	4.3k
Bing Xiang United States	31	3.4k 0.9×	655 0.6×	447 0.7×	537 1.5×	205 0.6×	88	3.9k
Xu Sun China	33	2.7k 0.7×	934 0.8×	443 0.7×	137 0.4×	120 0.3×	116	3.3k
Yi Tay Singapore	26	2.1k 0.5×	680 0.6×	954 1.5×	152 0.4×	169 0.5×	71	3.0k
Huanbo Luan China	27	2.8k 0.7×	1.1k 0.9×	507 0.8×	112 0.3×	125 0.4×	75	3.6k
Chenliang Li China	32	3.4k 0.9×	595 0.5×	1.5k 2.3×	240 0.7×	232 0.7×	134	4.5k

Countries citing papers authored by Dongyan Zhao

Since Specialization

Citations

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

Fields of papers citing papers by Dongyan Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongyan Zhao

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

Zhao, Dongyan, et al.. (2024). Firm digital investments and capacity utilisation: A perspective of factor inputs. Technological Forecasting and Social Change. 200. 123182–123182. 10 indexed citations

Tao, Chongyang, Xiubo Geng, Tao Shen, et al.. (2024). Synergistic Interplay between Search and Large Language Models for Information Retrieval. 9571–9583. 2 indexed citations

Zhang, Chen, Yuxuan Lai, Yansong Feng, et al.. (2023). Cross-Lingual Question Answering over Knowledge Base as Reading Comprehension. 2439–2452. 1 indexed citations

Ge, Tao, et al.. (2023). Smart Word Suggestions for Writing Assistance. 11212–11225.

He, Di, Yelong Shen, Tie‐Yan Liu, et al.. (2022). Finding the Dominant Winning Ticket in Pre-Trained Language Models. Findings of the Association for Computational Linguistics: ACL 2022. 1459–1472. 4 indexed citations

Zhu, Qingqing, et al.. (2021). Combining Curriculum Learning and Knowledge Distillation for Dialogue Generation. 1284–1295. 10 indexed citations

Gao, Shen, Xiuying Chen, Chang Liu, Dongyan Zhao, & Rui Yan. (2021). BioGen: Generating Biography Summary under Table Guidance on Wikipedia. 4752–4757.

Yu, Xiaohan, et al.. (2020). Towards Context-Aware Code Comment Generation. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 3938–3947. 12 indexed citations

Li, Mingzhe, Xiuying Chen, Shen Gao, et al.. (2020). VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles. 9360–9369. 46 indexed citations

10.

Li, Juntao, et al.. (2019). Are Training Samples Correlated? Learning to Generate Dialogue Responses with Multiple References. 3826–3835. 28 indexed citations

11.

Hu, Wenpeng, Bing Liu, Jinwen Ma, Dongyan Zhao, & Rui Yan. (2018). Aspect-based Question Generation. International Conference on Learning Representations. 11 indexed citations

12.

Fan, Feifan, Yansong Feng, & Dongyan Zhao. (2018). Multi-grained Attention Network for Aspect-Level Sentiment Classification. 3433–3442. 346 indexed citations breakdown →

13.

Lv, Chao, et al.. (2017). PKUICST at TREC 2017 Real-Time Summarization Track: Push Notifications and Email Digest.. Text REtrieval Conference.

14.

Hu, Sen, Lei Zou, Jeffrey Xu Yu, Haixun Wang, & Dongyan Zhao. (2017). Answering Natural Language Questions by Subgraph Matching over Knowledge Graphs. IEEE Transactions on Knowledge and Data Engineering. 30(5). 824–837. 178 indexed citations

15.

Yang, Honghui, et al.. (2015). WIP Event Detection System in TAC KBP 2015 Event Nugget Track.. Theory and applications of categories. 2 indexed citations

16.

Zong, Chengqing, Jian‐Yun Nie, Dongyan Zhao, & Yansong Feng. (2014). Natural Language Processing and Chinese Computing: Third CCF Conference, NLPCC 2014, Shenzhen, China, December 5-9, 2014. Proceedings. Springer eBooks. 4 indexed citations

17.

Zhao, Dongyan. (2012). Chinese News Event Ontology Construction and Auto-population. Computer Engineering and Science. 1 indexed citations

18.

Chen, Liwei, Yansong Feng, Yidong Chen, Lei Zou, & Dongyan Zhao. (2012). Towards Automatic Construction of Knowledge Bases from Chinese Online Resources. Meeting of the Association for Computational Linguistics. 67–72.

19.

Zhou, Ming, et al.. (2012). Natural Language Processing and Chinese Computing: First CCF Conference, NLPCC 2012, Beijing, China, October 31-November 5, 2012. Proceedings. DIAL (Catholic University of Leuven). 2 indexed citations

20.

Zhao, Dongyan. (2007). Method of collecting and analyzing news pages on Internet. Computer Engineering and Applications Journal.

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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