TY - GEN
T1 - Estimating aggregates over multiple sets
AU - Cohen, Edith
AU - Kaplan, Haim
PY - 2008
Y1 - 2008
N2 - Many datasets, including market basket data, text or hypertext documents, and measurement data collected in different nodes or time periods, are modeled as a collection of sets over a ground set of (weighted) items. We consider the problem of estimating basic aggregates such as the weight or selectivity of a subpopulation of the items. We extend classic summarization techniques based on sampling to this scenario when we have multiple sets and selection predicates based on membership in particular sets.
AB - Many datasets, including market basket data, text or hypertext documents, and measurement data collected in different nodes or time periods, are modeled as a collection of sets over a ground set of (weighted) items. We consider the problem of estimating basic aggregates such as the weight or selectivity of a subpopulation of the items. We extend classic summarization techniques based on sampling to this scenario when we have multiple sets and selection predicates based on membership in particular sets.
UR - http://www.scopus.com/inward/record.url?scp=67049114678&partnerID=8YFLogxK
U2 - 10.1109/ICDM.2008.110
DO - 10.1109/ICDM.2008.110
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AN - SCOPUS:67049114678
SN - 9780769535029
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 761
EP - 766
BT - Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
T2 - 8th IEEE International Conference on Data Mining, ICDM 2008
Y2 - 15 December 2008 through 19 December 2008
ER -