منابع مشابه
Weighted Random Sampling over Data Streams
In this work, we present a comprehensive treatment of weighted random sampling (WRS) over data streams. More precisely, we examine two natural interpretations of the item weights, describe an existing algorithm for each case ([2,4]), discuss sampling with and without replacement and show adaptations of the algorithms for several WRS problems and evolving data streams.
متن کاملOptimal Random Sampling from Distributed Streams Revisited
We give an improved algorithm for drawing a random sample from a large data stream when the input elements are distributed across multiple sites which communicate via a central coordinator. At any point in time the set of elements held by the coordinator represent a uniform random sample from the set of all the elements observed so far. When compared with prior work, our algorithms asymptotical...
متن کاملKSample: Dynamic Sampling Over Unbounded Data Streams
Data sampling over data streams is common practice to allow the analysis of data in real-time. However, sampling over data streams becomes complex when the stream does not fit in memory, and worse yet, when the length of the stream is unknown. A well-known technique for sampling data streams is the Reservoir Sampling. It requires a fixed-size reservoir that corresponds to the resulting sample s...
متن کاملWeighted Sampling Without Replacement from Data Streams
Weighted sampling without replacement has proved to be a very important tool in designing new algorithms. Efraimidis and Spirakis (IPL 2006) presented an algorithm for weighted sampling without replacement from data streams. Their algorithm works under the assumption of precise computations over the interval [0, 1]. Cohen and Kaplan (VLDB 2008) used similar methods for their bottom-k sketches. ...
متن کاملStratified Reservoir Sampling over Heterogeneous Data Streams
Reservoir sampling is a well-known technique for random sampling over data streams. In many streaming applications, however, an input stream may be naturally heterogeneous, i.e., composed of substreams whose statistical properties may also vary considerably. For this class of applications, the conventional reservoir sampling technique does not guarantee a statistically sufficient number of tupl...
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ژورنال
عنوان ژورنال: Advances in Electrical and Electronic Engineering
سال: 2011
ISSN: 1804-3119,1336-1376
DOI: 10.15598/aeee.v9i1.33