Dingming Wu

65 papers receiving 2.2k citations

Dingming Wu's Hit Papers

Spatial keyword query processing 2013 · 254 citations
2540+5+11Years since publication100200300400

Peers

Dingming Wu
Comparison fields: 5 of 113
  • Geography, Planning and Development 755
  • Signal Processing 1.3k
  • Computer Networks and Communications 823
  • Transportation 195
  • Inorganic Chemistry 315
Replace Michael Cafarella with:
Michael Cafarella United States
Ray R. Larson United States
Bowen Yu China
George Ferguson United States
Steffen Koch Germany
Guiling Wang China
Huanhuan Cao China
Ramesh Krishnamurti United States
Seema Bawa India
Dingming Wu relative to Michael Cafarella United States Michael Cafarella's profile →
Citations per field
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Citations per year

Countries citing papers authored by Dingming Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dingming Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dingming Wu, 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 Dingming Wu Line = papers co-authored together Dingming Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Efficient retrieval of the top-k most relevant spatial web objects
Hit paper breakdown →
2009454
2
Spatial keyword query processing
Hit paper breakdown →
2013254
3 2015159
4 2011121
5 2011117
6 2012108
7 2021106
8 2012101
9 200388
10 200576
11 201463
12 200646
13 201941
14 201639
15 200134
16 201432
17 201427
18 201325
19 200224
20 201724

About Dingming Wu

Dingming Wu is a scholar working on Signal Processing, Computer Networks and Communications, Information Systems, Geography, Planning and Development and Inorganic Chemistry, having authored 68 papers that have together received 2.3k indexed citations. Recurring topics across this work include Data Management and Algorithms (28 papers), Geographic Information Systems Studies (18 papers), Advanced Database Systems and Queries (14 papers), Metal-Organic Frameworks: Synthesis and Applications (11 papers), Data Mining Algorithms and Applications (8 papers), Recommender Systems and Techniques (8 papers), Complex Network Analysis Techniques (8 papers) and Magnetism in coordination complexes (5 papers). The work is most often cited by research in Geography, Planning and Development (755 citations), Signal Processing (1.3k citations), Computer Networks and Communications (823 citations), Transportation (195 citations) and Inorganic Chemistry (315 citations). Dingming Wu has collaborated with scholars based in China, Hong Kong and Denmark. Frequent co-authors include Christian S. Jensen, Gao Cong, Man Lung Yiu, Lisi Chen, Can‐Zhong Lu, Nikos Mamoulis, Jin Gu, Michael Q. Zhang, Dongfang Wang and J. Y. Shi. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, Big Data Mining and Analytics, The VLDB Journal and Information Processing & Management.

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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