This map shows the geographic impact of Peifeng 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 Peifeng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peifeng Li more than expected).
This network shows the impact of papers produced by Peifeng 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 Peifeng Li. The network helps show where Peifeng Li may publish in the future.
Co-authorship network of co-authors of Peifeng Li
This figure shows the co-authorship network connecting the top 25 collaborators of Peifeng Li.
A scholar is included among the top collaborators of Peifeng 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 Peifeng Li. Peifeng Li is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Li, Peifeng, et al.. (2018). MCDTB: A Macro-level Chinese Discourse TreeBank. International Conference on Computational Linguistics. 3493–3504.5 indexed citations
Li, Peifeng, Qiaoming Zhu, Guodong Zhou, & Hongling Wang. (2016). Global Inference to Chinese Temporal Relation Extraction. International Conference on Computational Linguistics. 1451–1460.6 indexed citations
10.
Li, Peifeng, Qiaoming Zhu, & Guodong Zhou. (2014). Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction. International Conference on Computational Linguistics. 2161–2171.3 indexed citations
11.
Li, Peifeng, Qiaoming Zhu, & Guodong Zhou. (2013). Joint modeling of argument identification and role determination in Chinese event extraction with discourse-level information. International Joint Conference on Artificial Intelligence. 2120–2126.9 indexed citations
12.
Li, Peifeng, Qiaoming Zhu, & Guodong Zhou. (2013). Argument Inference from Relevant Event Mentions in Chinese Argument Extraction. Meeting of the Association for Computational Linguistics. 1477–1487.11 indexed citations
13.
Liu, Huanhuan, Shoushan Li, Guodong Zhou, Chu‐Ren Huang, & Peifeng Li. (2013). Joint modeling of news reader's and comment writer's emotions. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 511–515.17 indexed citations
14.
Li, Peifeng. (2012). Chinese text similarity method research by combining semantic analysis with statistics. Jisuanji yingyong yanjiu.1 indexed citations
15.
Li, Peifeng, et al.. (2012). Joint Modeling of Trigger Identification and Event Type Determination in Chinese Event Extraction. International Conference on Computational Linguistics. 1635–1652.7 indexed citations
16.
Li, Peifeng & Guodong Zhou. (2012). Employing Morphological Structures and Sememes for Chinese Event Extraction. International Conference on Computational Linguistics. 1619–1634.13 indexed citations
17.
Li, Peifeng, et al.. (2011). Using Context Inference to Improve Sentence Ordering for Multi-document Summarization. International Joint Conference on Natural Language Processing. 1055–1061.3 indexed citations
18.
Li, Peifeng, Jinhui Li, & Qiaoming Zhu. (2007). An Approach to Email Categorization with the ME Model.. The Florida AI Research Society. 229–234.2 indexed citations
19.
Li, Peifeng. (2006). Design of Fast Discovery System of Network Topology Based on OSPF. Jisuanji gongcheng.
20.
Li, Peifeng. (2004). Research of Han Character Internal Codes Recognition Algorithm in the Multi-lingual Environment. Zhongwen xinxi xuebao.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.