Xian-Ling Mao

3.0k total citations · 1 hit paper
112 papers, 1.6k citations indexed

About

Xian-Ling Mao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Xian-Ling Mao has authored 112 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Artificial Intelligence, 39 papers in Computer Vision and Pattern Recognition and 25 papers in Information Systems. Recurrent topics in Xian-Ling Mao's work include Topic Modeling (59 papers), Natural Language Processing Techniques (36 papers) and Multimodal Machine Learning Applications (28 papers). Xian-Ling Mao is often cited by papers focused on Topic Modeling (59 papers), Natural Language Processing Techniques (36 papers) and Multimodal Machine Learning Applications (28 papers). Xian-Ling Mao collaborates with scholars based in China, Singapore and United States. Xian-Ling Mao's co-authors include Wei Wei, Heyan Huang, Zewen Chi, Rong-Cheng Tu, Ding Zou, Furu Wei, Feida Zhu, Li Dong, Ziyang Wang and Song Xia and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.

In The Last Decade

Xian-Ling Mao

95 papers receiving 1.6k citations

Hit Papers

Multi-level Cross-view Contrastive Learning for Knowledge... 2022 2026 2023 2024 2022 25 50 75 100

Peers

Xian-Ling Mao
Comparison fields: 5 of 79
  • Artificial Intelligence 1.2k
  • Computer Vision and Pattern Recognition 608
  • Information Systems 443
  • Management Science and Operations Research 65
  • Computer Networks and Communications 49
Replace Da Cao with:
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Wenhu Chen United States
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Tushar Khot United States
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Da Cao China View profile →
Citations per field, relative to Xian-Ling Mao
Xian-Ling Mao · 1×
Citations per year, relative to Xian-Ling Mao
Xian-Ling Mao · 1×

Countries citing papers authored by Xian-Ling Mao

Since Specialization
Citations

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

Fields of papers citing papers by Xian-Ling Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xian-Ling Mao. 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 Xian-Ling Mao. The network helps show where Xian-Ling Mao may publish in the future.

Co-authorship network of co-authors of Xian-Ling Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Xian-Ling Mao. A scholar is included among the top collaborators of Xian-Ling Mao 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 Xian-Ling Mao. Xian-Ling Mao 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
# Work Indexed citations
1 1
2 0
3 0
4 1
5 1
6 0
7 2
8 0
9 8
10 11
11 0
12 29
13 47
14 2
15
Exploiting Repeated Behavior Pattern and Long-term Item dependency for Session-based Recommendation.
3
16 23
17
A Survey on Sentiment Lexicon Construction
2
18
A Novel Fast Framework for Topic Labeling Based on Similarity-preserved Hashing
3
19
Re-ranking voting-based answers by discarding user behavior biases
8
20
SSHLDA: A Semi-Supervised Hierarchical Topic Model
36

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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