Maofu Liu

56 papers receiving 805 citations

Peers

Maofu Liu
Comparison fields: 5 of 99
  • Computer Vision and Pattern Recognition 380
  • Artificial Intelligence 358
  • Industrial and Manufacturing Engineering 149
  • Computational Mechanics 81
  • Information Systems 70
Replace Yuting Wang with:
Yuting Wang China
Philippe Leray Belgium
Jiazhi Xia China
Danhua Xu China
Timothy X. Brown United States
Martín Carpio Mexico
Weili Guan China
Jing Peng United States
Sudhir P. Mudur Canada
Maofu Liu relative to Yuting Wang China Yuting Wang's profile →
Citations per field
00.5×2.8×
Yuting Wang · 1×
Citations per year

Countries citing papers authored by Maofu Liu

Since Specialization
Citations

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

Fields of papers citing papers by Maofu Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maofu Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Maofu Liu. A scholar is included among the top collaborators of Maofu Liu 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 Maofu Liu. Maofu Liu 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 1
2 1
3 2
4 8
5 1
6 1
7 11
8 23
9
Interest inference via structure-constrained multi-source multi-task learning
54
10
Recognizing Textual Entailment Based on Knowledge Topic Models
1
11
WUST at NTCIR-11 RITE-VAL System Validation Task
1
12
WUST at NTCIR-10 RITE-2 Task: Multiple Feature Approach to Chinese Textual Entailment.
2
13
WUST SVM-Based System at NTCIR-9 RITE Task
2
14
Wikipedia Article Content Based Query Expansion in IR4QA System.
2
15
Document Re-ranking via Wikipedia Articles for Definition/Biography Type Questions
1
16
TAC 2009 Update Summarization Task of WUST.
2
17
Progress and Problems in Microbial Carbonates Research
1
18
Question Analysis and Query Expansion in CS-CS IR4QA
2
19
An Image Retrieval System Based on IGA
1
20 4

About Maofu Liu

Maofu Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 59 papers that have together received 839 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Advanced Image and Video Retrieval Techniques (16 papers) and Advanced Text Analysis Techniques (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (380 citations), Industrial and Manufacturing Engineering (149 citations) and Artificial Intelligence (358 citations). Maofu Liu has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Huijun Hu, Liqiang Nie, Jing Tian, Weili Guan, Lingjun Li, Luming Zhang, Jianhua Dai, Ya Liu, Zhao Liu and Zehao Xue. Their work appears in journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Image Processing and Information Sciences.

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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