Byron J. Gao
- Signal Processing top 10%
- Data Management and Algorithms 11
- Time Series Analysis and Forecasting 5
- Artificial Intelligence top 5%
- Data Stream Mining Techniques 6
- Advanced Clustering Algorithms Research 5
- Information Systems top 5%
- Web Data Mining and Analysis 10
- Data Mining Algorithms and Applications 8
- Recommender Systems and Techniques 5
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- Complex Network Analysis Techniques 6
- Co-authors
- Martin EsterLi GuoPeng ZhangXingquan ZhuShuaiqiang WangJun MaJiankai SunPeng Wang
- Journals
- Neurocomputing (1 paper)IEEE Transactions on Knowledge and Data Engineering (5 papers)ACM SIGMOD Record (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Byron J. Gao
44 papers receiving 452 citations
Peers
Comparison fields: 5 of 53
- Signal Processing 100
- Artificial Intelligence 284
- Information Systems 198
- Statistical and Nonlinear Physics 61
- Computer Networks and Communications 96
Countries citing papers authored by Byron J. Gao
This map shows the geographic impact of Byron J. Gao'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 Byron J. Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Byron J. Gao more than expected).
Fields of papers citing papers by Byron J. Gao
This network shows the impact of papers produced by Byron J. Gao. 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 Byron J. Gao. The network helps show where Byron J. Gao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Byron J. Gao, 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 | 2022 | 1 | |
| 2 | 2019 | 2 | |
| 3 | 2017 | 1 | |
| 4 | 2015 | 5 | |
| 5 | 2014 | 42 | |
| 6 | 2014 | 6 | |
| 7 | 2013 | 3 | |
| 8 | 2013 | 10 | |
| 9 | 2012 | 1 | |
| 10 | 2012 | 11 | |
| 11 | 2012 | 0 | |
| 12 | 2011 | 3 | |
| 13 | 2011 | 5 | |
| 14 | 2011 | 2 | |
| 15 | 2011 | 5 | |
| 16 | 2011 | 6 | |
| 17 | Utilizing User-input Contextual Terms for Query Disambiguation | 2010 | 3 |
| 18 | The Case for a Structured Approach to Managing Unstructured Data. | 2009 | 10 |
| 19 | 2008 | 27 | |
| 20 | User-Centric Research Challenges in Community Information Management Systems. | 2007 | 6 |
About Byron J. Gao
Byron J. Gao is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 46 papers that have together received 479 indexed citations. Recurring topics across this work include Data Management and Algorithms (11 papers), Web Data Mining and Analysis (10 papers), Data Mining Algorithms and Applications (8 papers), Complex Network Analysis Techniques (6 papers), Data Stream Mining Techniques (6 papers), Recommender Systems and Techniques (5 papers), Advanced Clustering Algorithms Research (5 papers) and Time Series Analysis and Forecasting (5 papers). The work is most often cited by research in Signal Processing (100 citations), Artificial Intelligence (284 citations) and Information Systems (198 citations). Byron J. Gao has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Martin Ester, Li Guo, Peng Zhang, Xingquan Zhu, Shuaiqiang Wang, Jun Ma, Jiankai Sun, Peng Wang, Zengjian Hu and Boaz Ben‐Moshe. Their work appears in journals such as Neurocomputing, IEEE Transactions on Knowledge and Data Engineering and ACM SIGMOD Record.
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.