Ruxia Liang

545 citations
16 papers · 414 · h-index 9

Impact in

Papers in

Ruxia Liang

14 papers receiving 396 citations

Peers

Ruxia Liang
Comparison fields: 5 of 64
  • Management Science and Operations Research 300
  • Statistics and Probability 63
  • Control and Systems Engineering 132
  • Artificial Intelligence 116
  • Information Systems and Management 23
Replace Xia Liang with:
Xia Liang China
Jiapeng Liu China
Juan Carlos Leyva López Mexico
Fengjie Wu Australia
B.K. Mohanty India
Haitham A. El-Ghareeb Egypt
Yongming Song China
Gao-Feng Yu China
Ruxia Liang relative to Xia Liang China Xia Liang's profile →
Citations per field
00.5×1.5×2.1×
Xia Liang · 1×
Citations per year

Countries citing papers authored by Ruxia Liang

Since Specialization
Citations

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

Fields of papers citing papers by Ruxia Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Ruxia Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ruxia Liang Line = papers co-authored together Ruxia Liang links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201981
2 201770
3 201668
4 201764
5 201737
6 201936
7 202223
8 200013
9 20188
10 20255
11 20233
12 20173
13 20242
14 20201
15 20250
16 20210

About Ruxia Liang

Ruxia Liang is a scholar working on Management Science and Operations Research, Artificial Intelligence, Control and Systems Engineering, Information Systems and Sociology and Political Science, having authored 16 papers that have together received 414 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (7 papers), Optimization and Mathematical Programming (4 papers), Recommender Systems and Techniques (3 papers), Technology Adoption and User Behaviour (2 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers), Advanced Bandit Algorithms Research (2 papers), Image Retrieval and Classification Techniques (2 papers) and Digital Marketing and Social Media (2 papers). The work is most often cited by research in Management Science and Operations Research (300 citations), Statistics and Probability (63 citations), Control and Systems Engineering (132 citations), Artificial Intelligence (116 citations) and Information Systems and Management (23 citations). Ruxia Liang has collaborated with scholars based in China, Australia and United Arab Emirates. Frequent co-authors include Jian‐qiang Wang, Hong‐yu Zhang, Lin Li, N. O. Nawari, Qian Zhang, Jie Lü, Zhiping Hou, X. Yuan, Junbo Li and Xiaoxuan Shen. Their work appears in journals such as Knowledge-Based Systems, International Journal of Fuzzy Systems, Neural Computing and Applications, Canadian Geotechnical Journal and Symmetry.

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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