Online Data Summarization
Online Data Summarization is a streaming algorithmic framework that continuously condenses high-volume, time-ordered data streams into compact, interpretable summaries by incrementally updating summary structures under strict space and time constraints.
78
Publications
5.1K
Citations
232
Authors
110
Institutions
Publications per year
2017–2026
24
Variants
Streaming Data Summarization
Parents
78
Space-efficient online computation of quantile summaries
Michael B. Greenwald, Sanjeev Khanna · 2001 · 456 citations
Streaming submodular maximization
Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi et al. · 2014 · 306 citations
Quasi Real-Time Summarization for Consumer Videos
Bin Zhao, Eric P. Xing · 2014 · 272 citations · Full text
Summarizing sporting events using twitter
Jeffrey Nichols, Jalal Mahmud, Clemens Drews · 2012 · 242 citations
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110
Carnegie Mellon University
Pittsburgh, United States
4 h-index
6 publications
805 citations
IBM (United States)
Armonk, United States
4 h-index
6 publications
934 citations
University of California, Riverside
Riverside, United States
3 h-index
6 publications
184 citations
Arizona State University
Tempe, United States
3 h-index
6 publications
95 citations

University of Colorado Colorado Springs
Colorado Springs, United States
3 h-index
6 publications
779 citations

McGill University
Montreal, Canada
3 h-index
5 publications
140 citations
The Ohio State University
Columbus, United States
3 h-index
6 publications
261 citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
2 h-index
2 publications
122 citations
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TKDE · 6 publications · 355 citations
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Repository · 3 publications · 40 citations
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2 publications · 78 citations
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TKDD · 2 publications · 104 citations
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2 publications · 55 citations
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