Dong Xin

5.2k citations
81 papers · 3.8k · 1 hit paper · h-index 32

Impact in

Papers in

Dong Xin

79 papers receiving 3.6k citations

Dong Xin's Hit Papers

Frequent pattern mining: current status and future directions 2007 · 1.0k citations
1.0k0+6+12Years since publication2505007501000

Peers

Dong Xin
Comparison fields: 5 of 115
  • Signal Processing 1.3k
  • Information Systems 2.1k
  • Artificial Intelligence 1.9k
  • Management Science and Operations Research 646
  • Computer Networks and Communications 1.1k
Replace Roberto J. Bayardo with:
Roberto J. Bayardo United States
Wilfred Ng Hong Kong
Sihem Amer-Yahia United States
Raffaele Perego Italy
Panos Kalnis Saudi Arabia
Meichun Hsu United States
Claudio Carpineto Italy
Giovanni Romano Italy
Fabian M. Suchanek Germany
Dayne Freitag United States
Dong Xin relative to Roberto J. Bayardo United States Roberto J. Bayardo's profile →
Citations per field
00.5×10×13×
Roberto J. Bayardo · 1×
Citations per year

Countries citing papers authored by Dong Xin

Since Specialization
Citations

This map shows the geographic impact of Dong Xin'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 Dong Xin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong Xin more than expected).

Fields of papers citing papers by Dong Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dong Xin. 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 Dong Xin. The network helps show where Dong Xin may publish in the future.

Co-authors

The 25 scholars most cited alongside Dong Xin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dong Xin Line = papers co-authored together Dong Xin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Frequent pattern mining: current status and future directions
Hit paper breakdown →
20071045
2
Web-scale Data Integration: You can only afford to Pay As You Go
2007240
3 2012189
4
Mining compressed frequent-pattern sets
2005154
5 2005145
6 2011124
7 2012109
8 2003104
9 2011101
10 201396
11 201092
12 200682
13 200558
14 201158
15 200755
16 200854
17 200653
18 200648
19 200946
20 200645

About Dong Xin

Dong Xin is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Management Science and Operations Research, having authored 81 papers that have together received 3.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (27 papers), Advanced Database Systems and Queries (25 papers), Data Quality and Management (23 papers), Data Mining Algorithms and Applications (22 papers), Web Data Mining and Analysis (19 papers), Topic Modeling (8 papers), Rough Sets and Fuzzy Logic (8 papers) and Semantic Web and Ontologies (8 papers). The work is most often cited by research in Signal Processing (1.3k citations), Information Systems (2.1k citations), Artificial Intelligence (1.9k citations), Management Science and Operations Research (646 citations) and Computer Networks and Communications (1.1k citations). Dong Xin has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jiawei Han, Hong Cheng, Xifeng Yan, Divesh Srivastava, Kaushik Chakrabarti, Xiaolei Li, Surajit Chaudhuri, Alon Halevy, Jayant Madhavan and Zheng Shao. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Bacteriology, Journal of the American Medical Informatics Association, Bioinformatics 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.

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