@inproceedings{e4f38e25d9714d02a7af412434105fc1,

title = "Bottom-k sketches: Better and more efficient estimation of aggregates",

abstract = "A Bottom-k sketch is a summary of a set of items with nonnegative weights. Each such summary allows us to compute approximate aggregates over the set of items. Bottom-k sketches are obtained by associating with each item in a ground set an independent random rank drawn from a probability distribution that depends on the weight of the item. For each subset of interest, the bottom-k sketch is the set of the k minimum ranked items and their ranks. Bottom-k sketches have numerous applications. We develop and analyze data structures and estimators for bottom-k sketches to facilitate their deployment. We develop novel estimators and algorithms that show that they are a superior alternative to other sketching methods in both efficiency of obtaining the sketches and the accuracy of the estimates derived from the sketches.",

keywords = "Approximate query processing, Bottom-k, Sketches",

author = "Edith Cohen and Haim Kaplan",

year = "2007",

doi = "10.1145/1269899.1254926",

language = "אנגלית",

isbn = "1595936394",

series = "Performance Evaluation Review",

number = "1",

pages = "353--354",

booktitle = "SIGMETRICS'07 - Proceedings of the 2007 International Conference on Measurement and Modeling of Computer Systems",

edition = "1",

note = "null ; Conference date: 12-06-2007 Through 16-06-2007",

}