Peng-Hsuan Li

545 citations
7 papers · 312 indexed · h-index 4
Topics
Topic Modeling (7 papers)Natural Language Processing Techniques (4 papers)Biomedical Text Mining and Ontologies (3 papers)
Journals
Nucleic Acids ResearchBriefings in BioinformaticsInternational Joint Conference on Natural Language Processing
Partner nations
TaiwanUnited States

In The Last Decade

Peng-Hsuan Li

7 papers receiving 307 citations

Peers

Peng-Hsuan Li
Comparison fields: 5 of 50
  • Artificial Intelligence 289
  • Management Science and Operations Research 55
  • Molecular Biology 41
  • Information Systems 32
  • Computer Vision and Pattern Recognition 23
Replace Zhepei Wei with:
Zhepei Wei China
Prafulla Kumar Choubey United States
Q. Liu China
Chen-Tse Tsai United States
Yunzhi Yao China
Benfeng Xu China
Zeqiu Wu United States
Anne-Lyse Minard France
Runxin Xu China
Zhaocheng Zhu China
Peng-Hsuan Li relative to Zhepei Wei China Zhepei Wei's profile →
Citations per field
00.5×3.7×
Zhepei Wei · 1×
Citations per year

Countries citing papers authored by Peng-Hsuan Li

Since Specialization
Citations

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

Fields of papers citing papers by Peng-Hsuan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peng-Hsuan Li. 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 Peng-Hsuan Li. The network helps show where Peng-Hsuan Li may publish in the future.

Co-authorship network of co-authors of Peng-Hsuan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Peng-Hsuan Li. A scholar is included among the top collaborators of Peng-Hsuan Li 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 Peng-Hsuan Li. Peng-Hsuan Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
#WorkIndexed citations
1 2
2 9
3 38
4 257
5 1
6
Understanding and Improving Sequence-Labeling NER with Self-Attentive LSTMs
2
7
CKIP at IJCNLP-2017 Task 2: Neural Valence-Arousal Prediction for Phrases.
3

About Peng-Hsuan Li

Peng-Hsuan Li is a scholar working on Artificial Intelligence, Molecular Biology and Genetics, having authored 7 papers that have together received 312 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (4 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Artificial Intelligence (289 citations), Management Science and Operations Research (55 citations) and Health Informatics (2 citations). Peng-Hsuan Li has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Wei-Yun Ma, Tsu-Jui Fu, Huai‐Kuang Tsai, Hsueh‐Fen Juan, Chien‐Yu Chen, Jia‐Hsin Huang and Mu Yang. Their work appears in journals such as Nucleic Acids Research, Briefings in Bioinformatics and International Joint Conference on Natural Language Processing.

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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