Jack Wu
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Web Data Mining and Analysis
- Information Retrieval and Search Behavior
- Artificial Intelligence top 5%
- Topic Modeling
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Sentiment Analysis and Opinion Mining
- Natural Language Processing Techniques
Papers in
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- Information Retrieval and Search Behavior 7
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- Topic Modeling 4
- Co-authors
- Kam‐Fai Wong (7 shared papers)Robert W. P. Luk (7 shared papers)K. L. Kwok (4 shared papers)Kevin O’Gallagher (2 shared papers)Thomas Searle (2 shared papers)Daniel Sado (2 shared papers)John H. Xin (3 shared papers)James Teo (2 shared papers)
- Journals
- ACM Transactions on Information Systems (2 papers)Information Processing & Management (1 paper)Sensors (1 paper)Journal of Intelligent Manufacturing (1 paper)Coloration Technology (1 paper)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Jack Wu
11 papers receiving 576 citations
Jack Wu's Hit Papers
Peers
Comparison fields: 5 of 93
- Information Systems 248
- Artificial Intelligence 321
- Health Informatics 13
- Signal Processing 62
- Computer Science Applications 20
Countries citing papers authored by Jack Wu
This map shows the geographic impact of Jack Wu'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 Jack Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Wu more than expected).
Fields of papers citing papers by Jack Wu
This network shows the impact of papers produced by Jack Wu. 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 Jack Wu. The network helps show where Jack Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jack Wu, 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 | Interpreting TF-IDF term weights as making relevance decisions Hit paper breakdown → | 2008 | 545 |
| 2 | 2023 | 27 | |
| 3 | 2006 | 18 | |
| 4 | 2022 | 4 | |
| 5 | 2005 | 4 | |
| 6 | 2009 | 4 | |
| 7 | 2024 | 3 | |
| 8 | 2007 | 3 | |
| 9 | 2023 | 2 | |
| 10 | 2006 | 2 | |
| 11 | 2019 | 1 | |
| 12 | 2023 | 0 |
About Jack Wu
Jack Wu is a scholar working on Information Systems, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Signal Processing and Cardiology and Cardiovascular Medicine, having authored 12 papers that have together received 613 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (7 papers), Topic Modeling (4 papers), Color Science and Applications (3 papers), Data Management and Algorithms (3 papers), Heart Failure Treatment and Management (2 papers), Industrial Vision Systems and Defect Detection (2 papers), Cardiovascular Function and Risk Factors (2 papers) and Cardiac Valve Diseases and Treatments (1 paper). The work is most often cited by research in Information Systems (248 citations), Artificial Intelligence (321 citations), Health Informatics (13 citations), Signal Processing (62 citations) and Computer Science Applications (20 citations). Jack Wu has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include Kam‐Fai Wong, Robert W. P. Luk, K. L. Kwok, Kevin O’Gallagher, Thomas Searle, Daniel Sado, John H. Xin, James Teo, Richard Dobson and M. J. Ryan. Their work appears in journals such as ACM Transactions on Information Systems, Information Processing & Management, Sensors, Journal of Intelligent Manufacturing and Coloration Technology.
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.