Piji Li
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Advanced Graph Neural Networks
- Text and Document Classification Technologies
- Information Systems top 2%
- Recommender Systems and Techniques
Papers in
-
- Topic Modeling 47
- Natural Language Processing Techniques 35
- Advanced Text Analysis Techniques 9
- Speech and dialogue systems 6
- Text and Document Classification Technologies 6
-
- Multimodal Machine Learning Applications 16
- Advanced Image and Video Retrieval Techniques 11
- Image Retrieval and Classification Techniques 6
Piji Li
63 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 1.2k
- Information Systems 381
- Computer Vision and Pattern Recognition 261
- Management Science and Operations Research 68
- General Social Sciences 17
Countries citing papers authored by Piji Li
This map shows the geographic impact of Piji 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 Piji Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Piji Li more than expected).
Fields of papers citing papers by Piji Li
This network shows the impact of papers produced by Piji 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 Piji Li. The network helps show where Piji Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Piji Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2026 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 8 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 2 | |
| 12 | 2023 | 31 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 0 | |
| 15 | 2022 | 1 | |
| 16 | 2021 | 60 | |
| 17 | 2021 | 10 | |
| 18 | Incorporating Pseudo-Parallel Data for Quantifiable Sequence Editing. | 2018 | 1 |
| 19 | 2017 | 113 | |
| 20 | Abstractive Multi-Document Summarization via Phrase Selection and | 2015 | 2 |
About Piji Li
Piji Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing and General Social Sciences, having authored 72 papers that have together received 1.4k indexed citations. Recurring topics across this work include Topic Modeling (47 papers), Natural Language Processing Techniques (35 papers), Multimodal Machine Learning Applications (16 papers), Advanced Image and Video Retrieval Techniques (11 papers), Advanced Text Analysis Techniques (9 papers), Speech and dialogue systems (6 papers), Image Retrieval and Classification Techniques (6 papers) and Text and Document Classification Technologies (6 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Information Systems (381 citations), Computer Vision and Pattern Recognition (261 citations), Management Science and Operations Research (68 citations) and General Social Sciences (17 citations). Piji Li has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Lidong Bing, Wai Lam, Zhaochun Ren, Zihao Wang, Wai Lam, Xin Li, Maarten de Rijke, Shangsong Liang, Yi Liao and Weiwei Guo. Their work appears in journals such as Knowledge-Based Systems, Big Data Mining and Analytics, Water, Empirical Software Engineering and Journal of Systems and Software.
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.