Wei Ding

6.9k citations
188 papers · 5.1k · 1 hit paper · h-index 33

Impact in

    • Data Stream Mining Techniques
    • Machine Learning and Data Classification
    • Anomaly Detection Techniques and Applications
    • Text and Document Classification Technologies
    • Data Mining Algorithms and Applications

Papers in

Wei Ding

175 papers receiving 4.9k citations

Wei Ding's Hit Papers

Data mining with big data 2013 · 1.9k citations
1.9k0+4+8Years since publication50010001.5k

Peers

Wei Ding
Comparison fields: 5 of 174
  • Artificial Intelligence 2.6k
  • Information Systems 1.3k
  • Computer Vision and Pattern Recognition 1.1k
  • Signal Processing 521
  • Management Information Systems 366
Replace Joshua Zhexue Huang with:
Joshua Zhexue Huang China
Raymond Y.K. Lau Hong Kong
Pádraig Cunningham Ireland
Donato Malerba Italy
Zhongzhi Shi China
Xiaoyong Du China
Ali Selamat Malaysia
Xiangrui Meng China
Ali Ghodsi Canada
Alfredo Cuzzocrea Italy
Wei Ding relative to Joshua Zhexue Huang China Joshua Zhexue Huang's profile →
Citations per field
00.5×1.5×1.9×
Joshua Zhexue Huang · 1×
Citations per year

Countries citing papers authored by Wei Ding

Since Specialization
Citations

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

Fields of papers citing papers by Wei Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 188 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Data mining with big data
Hit paper breakdown →
20131907
2 2012230
3 2016121
4 2011114
5
Online Streaming Feature Selection
201096
6 202192
7 201992
8 201479
9 201169
10 201866
11 201166
12 201262
13 201662
14 201459
15 201455
16 200855
17 201354
18 201950
19 201650
20 201949

About Wei Ding

Wei Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing and Computer Networks and Communications, having authored 188 papers that have together received 5.1k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (20 papers), Anomaly Detection Techniques and Applications (17 papers), Topic Modeling (15 papers), Face and Expression Recognition (14 papers), Machine Learning and Data Classification (14 papers), Natural Language Processing Techniques (12 papers), Data Management and Algorithms (11 papers) and Data Stream Mining Techniques (11 papers). The work is most often cited by research in Artificial Intelligence (2.6k citations), Information Systems (1.3k citations), Computer Vision and Pattern Recognition (1.1k citations), Signal Processing (521 citations) and Management Information Systems (366 citations). Wei Ding has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Xindong Wu, Xingquan Zhu, Gongqing Wu, Kui Yu, T. F. Stepinski, Melissa S. Morabito, Jian Pei, Yang Mu, Hao Wang and Ping Chen. Their work appears in journals such as Applied Intelligence, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Knowledge Discovery from Data, IEEE Intelligent Systems and Data Mining and Knowledge Discovery.

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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