ScholarIQanswers from OpenAlex
Data Stream Mining Techniques
TopicLeading institutions, researchers & key papers
Data Stream Mining Techniques is a topic indexed in ScholarIQ from OpenAlex.
What is known about Data Stream Mining Techniques?
ScholarIQrecord summary
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.
How many works does Data Stream Mining Techniques have?
ScholarIQindexed works
Data Stream Mining Techniques has 61 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.
What is the OpenAlex record for Data Stream Mining Techniques?
ScholarIQopenalex
The OpenAlex for Data Stream Mining Techniques is on the source record.
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
Incremental Linear Discriminant Analysis for Classification of Data Streams
Shaoning Pang, Seiichi Ozawa, Nikola Kasabov
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
Database Meets Deep Learning
Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Kian‐Lee Tan
Analyzing concept drift and shift from sample data
Geoffrey I. Webb, Loong Kuan Lee, Bart Goethals, François Petitjean
Where is Data Stream Mining Techniques research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on Data Stream Mining Techniques is open access?
ScholarIQopen access share
67%OPEN ACCESS