Jack Wu
Impact in
- Information Systems top 5%
- Web Data Mining and Analysis
- Recommender Systems and Techniques
- 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 8
- Web Data Mining and Analysis 1
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- Topic Modeling 4
- Bayesian Modeling and Causal Inference 1
- Co-authors
- Kam‐Fai Wong (8 shared papers)Robert W. P. Luk (8 shared papers)K. L. Kwok (4 shared papers)Richard Grocott‐Mason (1 shared paper)Kevin O’Gallagher (2 shared papers)Ranu Baral (2 shared papers)John H. Xin (3 shared papers)Thomas Searle (2 shared papers)
- Journals
- ACM Transactions on Information Systems (2 papers)Information Processing & Management (2 papers)European Journal of Heart Failure (1 paper)Journal of Intelligent Manufacturing (1 paper)Coloration Technology (1 paper)
- Partner nations
- Hong KongUnited StatesChina
In The Last Decade
Jack Wu
12 papers receiving 666 citations
Jack Wu's Hit Papers
Peers
Comparison fields: 5 of 95
- Information Systems 292
- Artificial Intelligence 372
- Health Informatics 13
- Signal Processing 73
- Statistical and Nonlinear Physics 47
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 | 621 |
| 2 | 2023 | 35 | |
| 3 | 2006 | 22 | |
| 4 | 2024 | 5 | |
| 5 | 2005 | 5 | |
| 6 | 2022 | 4 | |
| 7 | 2009 | 4 | |
| 8 | 2023 | 3 | |
| 9 | 2007 | 3 | |
| 10 | 2006 | 2 | |
| 11 | 2019 | 1 | |
| 12 | 2012 | 1 | |
| 13 | 2023 | 0 |
About Jack Wu
Jack Wu is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Atomic and Molecular Physics, and Optics and Cardiology and Cardiovascular Medicine, having authored 13 papers that have together received 706 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (8 papers), Topic Modeling (4 papers), Data Management and Algorithms (4 papers), Color Science and Applications (3 papers), Industrial Vision Systems and Defect Detection (2 papers), Heart Failure Treatment and Management (2 papers), Web Data Mining and Analysis (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Information Systems (292 citations), Artificial Intelligence (372 citations), Health Informatics (13 citations), Signal Processing (73 citations) and Statistical and Nonlinear Physics (47 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, Richard Grocott‐Mason, Kevin O’Gallagher, Ranu Baral, John H. Xin, Thomas Searle, Daniel Sado and Narbeh Melikian. Their work appears in journals such as ACM Transactions on Information Systems, Information Processing & Management, European Journal of Heart Failure, 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.