Bee-Chung Chen
Impact in
- Information Systems top 0.5%
- Recommender Systems and Techniques
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- Advanced Bandit Algorithms Research
Papers in ⓘ
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- Advanced Bandit Algorithms Research 12
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- Recommender Systems and Techniques 19
- Expert finding and Q&A systems 4
- Data Mining Algorithms and Applications 4
- Co-authors
- Deepak Agarwal (18 shared papers)Pradheep Elango (7 shared papers)Kristen LeFevre (4 shared papers)Raghu Ramakrishnan (6 shared papers)Ashwin Machanavajjhala (2 shared papers)Daniel Kifer (2 shared papers)Bo Long (2 shared papers)Deepak Agarwal (5 shared papers)
- Journals
- Communications of the ACM (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)Data Mining and Knowledge Discovery (1 paper)The VLDB Journal (1 paper)NTUR (臺灣機構典藏) (1 paper)
- Partner nations
- United StatesUnited KingdomTaiwan
In The Last Decade
Bee-Chung Chen
40 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Information Systems 1.0k
- Management Science and Operations Research 460
- Artificial Intelligence 1.0k
- Computer Science Applications 105
- Computational Mathematics 11
Countries citing papers authored by Bee-Chung Chen
This map shows the geographic impact of Bee-Chung Chen'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 Bee-Chung Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bee-Chung Chen more than expected).
Fields of papers citing papers by Bee-Chung Chen
This network shows the impact of papers produced by Bee-Chung Chen. 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 Bee-Chung Chen. The network helps show where Bee-Chung Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Bee-Chung Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Regression-based latent factor models Hit paper breakdown → | 2009 | 360 |
| 2 | 2010 | 184 | |
| 3 | 2009 | 102 | |
| 4 | Privacy skyline: privacy with multidimensional adversarial knowledge | 2007 | 97 |
| 5 | 2009 | 87 | |
| 6 | 2009 | 84 | |
| 7 | Online Models for Content Optimization | 2008 | 71 |
| 8 | Example-driven design of efficient record matching queries | 2007 | 68 |
| 9 | 2009 | 65 | |
| 10 | 2011 | 54 | |
| 11 | 2016 | 52 | |
| 12 | 2010 | 43 | |
| 13 | 2017 | 41 | |
| 14 | 2011 | 40 | |
| 15 | 2016 | 38 | |
| 16 | Prediction cubes | 2005 | 35 |
| 17 | 2011 | 34 | |
| 18 | 1972 | 33 | |
| 19 | 2012 | 32 | |
| 20 | 2015 | 27 |
About Bee-Chung Chen
Bee-Chung Chen is a scholar working on Management Science and Operations Research, Information Systems, Artificial Intelligence, Computer Science Applications and Signal Processing, having authored 40 papers that have together received 1.8k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (19 papers), Advanced Bandit Algorithms Research (12 papers), Data Stream Mining Techniques (6 papers), Data Management and Algorithms (5 papers), Advanced Database Systems and Queries (5 papers), Expert finding and Q&A systems (4 papers), Data Mining Algorithms and Applications (4 papers) and Privacy-Preserving Technologies in Data (4 papers). The work is most often cited by research in Information Systems (1.0k citations), Management Science and Operations Research (460 citations), Artificial Intelligence (1.0k citations), Computer Science Applications (105 citations) and Computational Mathematics (11 citations). Bee-Chung Chen has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include Deepak Agarwal, Pradheep Elango, Kristen LeFevre, Raghu Ramakrishnan, Ashwin Machanavajjhala, Daniel Kifer, Bo Long, Deepak Agarwal, Xuanhui Wang and Surajit Chaudhuri. Their work appears in journals such as Communications of the ACM, ACM Transactions on Knowledge Discovery from Data, Data Mining and Knowledge Discovery, The VLDB Journal and NTUR (臺灣機構典藏).
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.