Sampling For Summarization
Sampling for Summarization is a data selection methodology that distinguishes itself by identifying and extracting a representative subset of data points from a larger dataset to facilitate efficient and accurate summarization, preserving critical information while reducing computational complexity.
21
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1.9K
Citations
45
Authors
22
Institutions
Publications per year
2017–2026
4
Parents
21
Improved histograms for selectivity estimation of range predicates
Viswanath Poosala, Peter J. Haas, Yannis Ioannidis et al. · 1996 · 559 citations
Improved histograms for selectivity estimation of range predicates
Viswanath Poosala, Peter J. Haas, Yannis Ioannidis et al. · ACM SIGMOD Record · 1996 · 184 citations
Christopher R. Palmer, Christos Faloutsos · ACM SIGMOD Record · 2000 · 137 citations
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AT&T (United States)
Bedminster, United States
5 h-index
10 publications
327 citations

Tel Aviv University
Tel Aviv, Israel
4 h-index
4 publications
637 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
396 citations
Arizona State University
Tempe, United States
2 h-index
3 publications
44 citations
University of Illinois System
Urbana, United States
2 h-index
2 publications
32 citations
IBM Research - Almaden
San Jose, United States
2 h-index
3 publications
383 citations

Illinois Institute of Technology
Chicago, United States
2 h-index
4 publications
64 citations
Twitter (United States)
San Francisco, United States
1 h-index
1 publications
82 citations
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PVLDB · 6 publications · 235 citations
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3 publications · 392 citations
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1 publications · 10 citations
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DKE · 1 publications · 26 citations
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Conference · 1 publications · 32 citations
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