Xin Luna Dong
- Artificial Intelligence top 0.2%
- Management Science and Operations Research top 0.2%
- Information Systems top 0.5%
- Computer Networks and Communications top 1%
- Signal Processing top 1%
- Co-authors
- Alon HalevyDivesh SrivastavaShaohua SunKevin MurphyEvgeniy GabrilovichLaure Berti‐ÉquilleJayant MadhavanGeremy Heitz
- Topics
- Data Quality and Management (35 papers)Web Data Mining and Analysis (24 papers)Topic Modeling (18 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputer Science Applications
- Journals
- BioinformaticsSensorsSolar Energy
- Partner nations
- United StatesChinaGermany
In The Last Decade
Xin Luna Dong
90 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 2.6k
- Management Science and Operations Research 1.6k
- Information Systems 1.3k
- Computer Networks and Communications 935
- Signal Processing 544
Countries citing papers authored by Xin Luna Dong
This map shows the geographic impact of Xin Luna Dong'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 Xin Luna Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Luna Dong more than expected).
Fields of papers citing papers by Xin Luna Dong
This network shows the impact of papers produced by Xin Luna Dong. 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 Xin Luna Dong. The network helps show where Xin Luna Dong may publish in the future.
Co-authorship network of co-authors of Xin Luna Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Xin Luna Dong. A scholar is included among the top collaborators of Xin Luna Dong 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 Xin Luna Dong. Xin Luna Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 17 | |
| 7 | 25 | |
| 8 | 6 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | 14 | |
| 12 | 30 | |
| 13 | 17 | |
| 14 | 1 | |
| 15 | Functional Dependency Generation and Applications in Pay-As-You-Go Data Integration Systems. | 28 |
| 16 | 143 | |
| 17 | Answering Structured Queries on Unstructured Data. | 30 |
| 18 | Structured Data Meets the Web: A Few Observations | 25 |
| 19 | A Platform for Personal Information Management and Integration. | 96 |
| 20 | Malleable ⁄ Schemas: A Preliminary Report | 16 |
About Xin Luna Dong
Xin Luna Dong is a scholar working on Management Science and Operations Research, Information Systems and Artificial Intelligence, having authored 97 papers that have together received 3.9k indexed citations. Recurring topics across this work include Data Quality and Management (35 papers), Web Data Mining and Analysis (24 papers) and Topic Modeling (18 papers). The work is most often cited by research in Management Science and Operations Research (1.6k citations), Artificial Intelligence (2.6k citations) and Computer Science Applications (392 citations). Xin Luna Dong has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Alon Halevy, Divesh Srivastava, Shaohua Sun, Kevin Murphy, Evgeniy Gabrilovich, Laure Berti‐Équille, Jayant Madhavan, Geremy Heitz, Ni Lao and Wei Zhang. Their work appears in journals such as Bioinformatics, Sensors and Solar Energy.
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.