Stream Mining
Stream Mining is a computational paradigm that involves the continuous extraction of meaningful patterns and knowledge from high-velocity, time-varying data streams, distinguished by its requirement for real-time processing, limited memory usage, and single-pass analysis of transient data elements.
1.6K
Publications
133.9K
Citations
3.3K
Authors
1.1K
Institutions
Publications per year
2017–2026
507
Parents
1.6K
Data mining: concepts and techniques
Jiawei Han, Micheline Kamber · Choice Reviews Online · 2012 · 28.9K citations
Mining high-speed data streams
Pedro Domingos, Geoff Hulten · 2000 · 2.2K citations · Full text
A symbolic representation of time series, with implications for streaming algorithms
Jessica Lin, Eamonn Keogh, Stefano Lonardi et al. · 2003 · 1.8K citations
Mining time-changing data streams
Geoff Hulten, Laurie Spencer, Pedro Domingos · 2001 · 1.8K citations
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1.1K
IBM (United States)
Armonk, United States
33 h-index
79 publications
13.8K citations

Universidade do Porto
Porto, Portugal
26 h-index
49 publications
5K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
23 h-index
48 publications
3.6K citations
University of Technology Sydney
Sydney, Australia
20 h-index
67 publications
3.6K citations
Universidade de São Paulo
São Paulo, Brazil
19 h-index
46 publications
2.7K citations

Monash University
Melbourne, Australia
18 h-index
47 publications
4.8K citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
18 h-index
56 publications
2.3K citations

Sejong University
Seoul, South Korea
17 h-index
51 publications
2.3K citations
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61 publications · 3.4K citations
32
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57 publications · 2.8K citations
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TKDE · 36 publications · 3.6K citations
29
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32 publications · 2.2K citations
24
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25 publications · 2.6K citations
20
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