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Data Stream Mining Techniques
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the adaptation to concept drift in data streams, particularly in the context of ensemble learning, adaptive algorithms, and online learning. It addresses challenges such as change detection, class imbalance, and incremental learning in streaming data environments.
61
Works
IDs:OpenAlex
How has Data Stream Mining Techniques's publication output changed over time?
ScholarIQpublication output · 2005–2026
Output grew0% over the shown period — from 1 works in 2005 to 1 in 2026.
1
1
1
2
2
1
1
1
1
1
2005200920152016201820192020202120252026
What are the most-cited papers on Data Stream Mining Techniques?
ScholarIQmost cited works
Characterizing concept drift
Geoffrey I. Webb, Roy Hyde, Hong Cao, Hai Long Nguyen, François Petitjean
S121920818. 2016516 CitationsOPEN ACCESS
Incremental Linear Discriminant Analysis for Classification of Data Streams
Shaoning Pang, Seiichi Ozawa, Nikola Kasabov
S4210170378. 2005339 CitationsOPEN ACCESS
IOT based wearable sensor for diseases prediction and symptom analysis in healthcare sector
BalaAnand Muthu, C. B. Sivaparthipan, Gunasekaran Manogaran, Revathi Sundarasekar, Seifedine Kadry, A. Shanthini, A. Antony Dasel
S177487720. 2020239 Citations
Database Meets Deep Learning
Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Kian‐Lee Tan
S47508943. 2016149 CitationsOPEN ACCESS
Analyzing concept drift and shift from sample data
Geoffrey I. Webb, Loong Kuan Lee, Bart Goethals, François Petitjean
S121920818. 2018106 Citations
Where is Data Stream Mining Techniques research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
S121920818622
S4210170378339
S177487720239
S47508943149
S4208094960
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Data Stream Mining Techniques is open access?
ScholarIQopen access share
67%OPEN ACCESS
Gold
0%
Green
42%
Hybrid
17%
Bronze
8%
Closed
33%
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