Xiaohua Liu

4.2k total citations · 1 hit paper
89 papers, 2.2k citations indexed

About

Xiaohua Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Xiaohua Liu has authored 89 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 29 papers in Computer Vision and Pattern Recognition and 12 papers in Information Systems. Recurrent topics in Xiaohua Liu's work include Topic Modeling (30 papers), Natural Language Processing Techniques (25 papers) and Text and Document Classification Technologies (10 papers). Xiaohua Liu is often cited by papers focused on Topic Modeling (30 papers), Natural Language Processing Techniques (25 papers) and Text and Document Classification Technologies (10 papers). Xiaohua Liu collaborates with scholars based in China, United States and Australia. Xiaohua Liu's co-authors include Ming Zhou, Furu Wei, Long Jiang, Mo Yu, Tiejun Zhao, Ming Zhou, Shaodian Zhang, Xiaolong Wang, Ming Zhang and Zhaopeng Tu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Proceedings of the IEEE and Scientific Reports.

In The Last Decade

Xiaohua Liu

81 papers receiving 2.0k citations

Hit Papers

Target-dependent Twitter Sentiment Classification 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaohua Liu China 20 1.7k 486 290 215 125 89 2.2k
Paul Tarau United States 11 2.3k 1.3× 650 1.3× 190 0.7× 151 0.7× 61 0.5× 82 2.6k
Zheng Chen China 20 1.8k 1.0× 798 1.6× 287 1.0× 120 0.6× 50 0.4× 63 2.2k
Jian-Tao Sun China 24 1.8k 1.0× 1.0k 2.1× 409 1.4× 150 0.7× 86 0.7× 56 2.6k
Kuiyu Chang Singapore 19 795 0.5× 451 0.9× 195 0.7× 198 0.9× 84 0.7× 45 1.1k
Deepak Ravichandran United States 14 1.6k 0.9× 569 1.2× 235 0.8× 81 0.4× 43 0.3× 22 1.9k
Aliaksei Severyn Italy 18 1.7k 0.9× 509 1.0× 289 1.0× 52 0.2× 107 0.9× 30 1.9k
Bert Huang United States 18 766 0.4× 176 0.4× 228 0.8× 140 0.7× 75 0.6× 50 1.3k
Kaize Ding United States 17 924 0.5× 335 0.7× 134 0.5× 173 0.8× 134 1.1× 56 1.1k
Shangsong Liang China 26 1.1k 0.7× 838 1.7× 292 1.0× 255 1.2× 108 0.9× 98 1.6k
Julio Gonzalo Spain 23 1.6k 0.9× 700 1.4× 212 0.7× 137 0.6× 62 0.5× 98 2.0k

Countries citing papers authored by Xiaohua Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohua Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaohua Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaohua Liu. A scholar is included among the top collaborators of Xiaohua 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 Xiaohua Liu. Xiaohua 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
1.
Li, Rongyi, Xianli Liu, Caixu Yue, et al.. (2025). Swin-fusion: An adaptive multi-source information fusion framework for enhanced tool wear monitoring. Journal of Manufacturing Systems. 79. 435–454. 10 indexed citations
2.
Liu, Xiaohua, et al.. (2024). Periapical lesion detection in periapical radiographs using the latest convolutional neural network ConvNeXt and its integrated models. Scientific Reports. 14(1). 25429–25429. 7 indexed citations
3.
Wu, Zixuan, Xiaohua Liu, Kang Wei Tan, Xiaolei Yao, & Qinghua Peng. (2024). Integrated machine learning and Mendelian randomization reveal PALMD as a prognostic biomarker for nonspecific orbital inflammation. Scientific Reports. 14(1). 24020–24020.
4.
Yin, Ming, Xiaohua Liu, Liuyang Wang, & Guoliang He. (2023). Learning latent embedding via weighted projection matrix alignment for incomplete multi-view clustering. Information Sciences. 634. 244–258. 19 indexed citations
5.
Liu, Xiaohua, et al.. (2019). Low-light color image enhancement based on NSST. 26(5). 41. 3 indexed citations
6.
Tu, Zhaopeng, Zhengdong Lu, Yang Liu, Xiaohua Liu, & Hang Li. (2016). Coverage-based Neural Machine Translation.. arXiv (Cornell University). 37 indexed citations
7.
Liu, Xiaohua, et al.. (2013). Entity Linking for Tweets. Meeting of the Association for Computational Linguistics. 1. 1304–1311. 52 indexed citations
8.
Gao, Dehong, Furu Wei, Wenjie Li, Xiaohua Liu, & Ming Zhou. (2013). Cotraining based bilingual sentiment lexicon learning. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 26–28. 10 indexed citations
9.
Liu, Xiaohua, Yitong Li, Furu Wei, & Ming Zhou. (2012). Graph-Based Multi-Tweet Summarization using Social Signals. International Conference on Computational Linguistics. 1699–1714. 25 indexed citations
10.
Liu, Xiaohua, Furu Wei, & Ming Zhou. (2012). QuickView: NLP-based Tweet Search. Meeting of the Association for Computational Linguistics. 13–18. 3 indexed citations
11.
Li, Zhen, et al.. (2012). Study on Thermal Environment Evaluation in Data Centers. SHILAP Revista de lepidopterología. 33(5). 5–9. 10 indexed citations
12.
Jiang, Long, Mo Yu, Ming Zhou, Xiaohua Liu, & Tiejun Zhao. (2011). Target-dependent Twitter Sentiment Classification. Meeting of the Association for Computational Linguistics. 151–160. 578 indexed citations breakdown →
13.
Liu, Xiaohua, Shaodian Zhang, Furu Wei, & Ming Zhou. (2011). Recognizing Named Entities in Tweets. Meeting of the Association for Computational Linguistics. 359–367. 257 indexed citations
14.
Liu, Xiaohua, Kuan‐Ching Li, Ming Zhou, & Zhongyang Xiong. (2011). Collective semantic role labeling for tweets with clustering. International Joint Conference on Artificial Intelligence. 1832–1837. 23 indexed citations
15.
Scott, Matthew R., Xiaohua Liu, & Ming Zhou. (2011). Engkoo: Mining the Web for Language Learning. Meeting of the Association for Computational Linguistics. 44–49. 1 indexed citations
16.
Liu, Xiaohua. (2008). Digital image stabilization algorithm based on feature points tracking. Optical Technique. 1 indexed citations
17.
Cong, Gao, et al.. (2007). Mining sequential patterns and tree patterns to detect erroneous sentences. National Conference on Artificial Intelligence. 925–930. 16 indexed citations
18.
Liu, Xiaohua, Gao Cong, Ming Zhou, et al.. (2007). Detecting Erroneous Sentences using Automatically Mined Sequential Patterns. Meeting of the Association for Computational Linguistics. 81–88. 43 indexed citations
19.
Liu, Jianzhou, Tingting He, & Xiaohua Liu. (2003). Extracting Chinese Multi-Word Units from Large-Scale Balanced Corpus. Pacific Asia Conference on Language, Information, and Computation. 282–289. 5 indexed citations
20.
Zhang, Xinzheng & Xiaohua Liu. (1998). Stabilization Decomposition of Neutral Linear Time-Varying Interconnected Control Systems with the Multi-Group Multi-Delays. Control theory & applications. 1 indexed citations

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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