Lizhen Qu

2.9k citations
50 papers · 546 indexed · h-index 12
Topics
Topic Modeling (24 papers)Natural Language Processing Techniques (16 papers)Multimodal Machine Learning Applications (7 papers)

In The Last Decade

Lizhen Qu

45 papers receiving 524 citations

Peers

Lizhen Qu
Comparison fields: 5 of 61
  • Artificial Intelligence 386
  • Information Systems 183
  • Computer Vision and Pattern Recognition 76
  • Signal Processing 73
  • Software 57
Replace Edison Marrese-Taylor with:
Edison Marrese-Taylor Japan
Junyi Jessy Li United States
Wafaa S. El-Kassas Egypt
Jichuan Zeng Hong Kong
Seema Nagar India
S. M. M. Tahaghoghi Australia
Wanjun Zhong China
Bharat Ram Ambati India
Leo Gao Canada
Danilo Croce Italy
Lizhen Qu relative to Edison Marrese-Taylor Japan Edison Marrese-Taylor's profile →
Citations per field
00.5×2.7×
Edison Marrese-Taylor · 1×
Citations per year

Countries citing papers authored by Lizhen Qu

Since Specialization
Citations

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

Fields of papers citing papers by Lizhen Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lizhen Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Lizhen Qu. A scholar is included among the top collaborators of Lizhen Qu 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 Lizhen Qu. Lizhen Qu 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 0
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5 0
6 0
7 3
8 0
9 5
10 3
11 2
12 1
13 35
14 3
15 8
16 11
17 6
18 3
19
A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts
14
20
Sentence Level Subjectivity and Sentiment Analysis Experiments in NTCIR-7 MOAT Challenge.
9

About Lizhen Qu

Lizhen Qu is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 546 indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (16 papers) and Multimodal Machine Learning Applications (7 papers). The work is most often cited by research in Software (57 citations), Artificial Intelligence (386 citations) and Information Systems (183 citations). Lizhen Qu has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Gerhard Weikum, Georgiana Ifrim, Qiongkai Xu, Gholamreza Haffari, Paul Montague, Zhuang Li, Olivier De Vel, Zhenglu Yang, Jiawan Zhang and Shaodi You. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Clinical Epidemiology and IEEE Transactions on Software Engineering.

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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