Data Stream Mining
Data Stream Mining is a computational method that systematically extracts, analyzes, and interprets continuous, real-time flows of user-generated data from social media platforms to identify patterns, behaviors, and trends as they emerge, distinguishing it from batch-oriented data analysis techniques by its emphasis on temporal immediacy and sequential processing.
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Institutions
Publications per year
2017–2026
676
Parents
2.1K
Data mining: concepts and techniques
Jiawei Han, Micheline Kamber · Choice Reviews Online · 2012 · 28.9K citations
Top 10 algorithms in data mining
Xindong Wu, Vipin Kumar, J. R. Quinlan et al. · Knowledge and Information Systems · 2007 · 5.7K citations
Data mining and knowledge discovery: making sense out of data
U.M. Feyyad · IEEE Expert · 1996 · 4.7K citations
From Data Mining to Knowledge Discovery in Databases
1996 · 4.7K citations
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IBM (United States)
Armonk, United States
35 h-index
105 publications
18.1K citations
University of Illinois Urbana-Champaign
Urbana, United States
25 h-index
64 publications
38.6K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
23 h-index
52 publications
3.5K citations

Universidade do Porto
Porto, Portugal
20 h-index
35 publications
4.5K citations
Carnegie Mellon University
Pittsburgh, United States
20 h-index
48 publications
6.4K citations

Monash University
Melbourne, Australia
19 h-index
49 publications
4.7K citations
University of Technology Sydney
Sydney, Australia
17 h-index
41 publications
2.4K citations
University of Illinois Chicago
Chicago, United States
17 h-index
26 publications
7.3K citations
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41 publications · 2.1K citations
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TKDE · 32 publications · 3.6K citations
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36 publications · 2.2K citations
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24 publications · 7.2K citations
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Repository · 34 publications · 2K citations
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