Conghui Zhu

619 citations
34 papers · 239 indexed · h-index 9
Topics
Topic Modeling (22 papers)Natural Language Processing Techniques (22 papers)Multimodal Machine Learning Applications (5 papers)
Partner nations
ChinaJapanAustria

In The Last Decade

Conghui Zhu

32 papers receiving 224 citations

Peers

Conghui Zhu
Comparison fields: 5 of 44
  • Artificial Intelligence 211
  • Computer Vision and Pattern Recognition 90
  • Information Systems 16
  • Media Technology 14
  • Experimental and Cognitive Psychology 10
Replace Gustavo Aguilar with:
Gustavo Aguilar United States
Iñigo López-Gazpio Spain
Adrià Giménez Spain
Yftah Ziser United Kingdom
Ciro Martins Portugal
Vincent Claveau France
Belinda Zeng United States
Arianna Bisazza Netherlands
Srikar Appalaraju United States
Conghui Zhu relative to Gustavo Aguilar United States Gustavo Aguilar's profile →
Citations per field
00.5×
Gustavo Aguilar · 1×
Citations per year

Countries citing papers authored by Conghui Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Conghui Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Conghui Zhu

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 6
3 54
4 1
5 0
6 1
7 2
8 2
9 16
10 35
11 2
12 2
13
Hierarchical Phrase Table Combination for Machine Translation
1
14 10
15
Locally Training the Log-Linear Model for SMT
15
16
Expected Error Minimization with Ultraconservative Update for SMT
2
17 1
18 1
19 4
20
A Unified Tagging Approach to Text Normalization
13

About Conghui Zhu

Conghui Zhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 34 papers that have together received 239 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Natural Language Processing Techniques (22 papers) and Multimodal Machine Learning Applications (5 papers). The work is most often cited by research in Artificial Intelligence (211 citations), Computer Vision and Pattern Recognition (90 citations) and Media Technology (14 citations). Conghui Zhu has collaborated with scholars based in China, Japan and Austria. Frequent co-authors include Tiejun Zhao, Bing Xu, Zhen Li, Dequan Zheng, Chaoqun Duan, Lemao Liu, Xinchi Chen, Lei Cui, Furu Wei and Tiejun Zhao. Their work appears in journals such as IEEE Access, Sensors and Information Fusion.

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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