Tak W. Yan
- Information Systems top 1%
- Computer Networks and Communications top 2%
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Héctor García-MolinaUmeshwar DayalMatthew JacobsenYe ChenSurajit ChaudhuriJ. AnnevelinkJeonghee YiJie Li
- Topics
- Advanced Database Systems and Queries (8 papers)Data Management and Algorithms (6 papers)Web Data Mining and Analysis (4 papers)
- Journals
- ACM SIGMOD RecordACM Transactions on Database SystemsUSENIX Annual Technical Conference
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Tak W. Yan
21 papers receiving 707 citations
Peers
Comparison fields: 5 of 46
- Information Systems 487
- Computer Networks and Communications 439
- Artificial Intelligence 275
- Signal Processing 239
- Computer Vision and Pattern Recognition 81
Countries citing papers authored by Tak W. Yan
This map shows the geographic impact of Tak W. Yan'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 Tak W. Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tak W. Yan more than expected).
Fields of papers citing papers by Tak W. Yan
This network shows the impact of papers produced by Tak W. Yan. 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 Tak W. Yan. The network helps show where Tak W. Yan may publish in the future.
Co-authorship network of co-authors of Tak W. Yan
This figure shows the co-authorship network connecting the top 25 collaborators of Tak W. Yan. A scholar is included among the top collaborators of Tak W. Yan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tak W. Yan. Tak W. Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 14 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 35 | |
| 8 | 14 | |
| 9 | 30 | |
| 10 | Efficient Dissemination of Information on the Internet. | 6 |
| 11 | 230 | |
| 12 | Duplicate Removal in Information System Dissemination | 5 |
| 13 | SIFT: a tool for wide-area information dissemination | 164 |
| 14 | Duplicate Detection in Information Dissemination | 6 |
| 15 | 3 | |
| 16 | 39 | |
| 17 | 1 | |
| 18 | Integrating a Structured-Text Retrieval System with an Object-Oriented Database System | 27 |
| 19 | 108 | |
| 20 | 1 |
About Tak W. Yan
Tak W. Yan is a scholar working on Signal Processing, Computer Networks and Communications and Marketing, having authored 22 papers that have together received 832 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (8 papers), Data Management and Algorithms (6 papers) and Web Data Mining and Analysis (4 papers). The work is most often cited by research in Signal Processing (239 citations), Information Systems (487 citations) and Computer Networks and Communications (439 citations). Tak W. Yan has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Héctor García-Molina, Umeshwar Dayal, Matthew Jacobsen, Ye Chen, Surajit Chaudhuri, J. Annevelink, Jeonghee Yi, Jie Li, Ye Chen and Anton Schwaighofer. Their work appears in journals such as ACM SIGMOD Record, ACM Transactions on Database Systems and USENIX Annual Technical Conference.
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.