Weighted Random Sampling

Years and Authors of Summarized Original Work

• 2005; Efraimidis, Spirakis

Problem Definition

The problem of random sampling without replacement (RS) calls for the selection of m distinct random items out of a population of size n. If all items have the same probability to be selected, the problem is known as uniform RS. Uniform random sampling in one pass is discussed in [1, 6, 11]. Reservoir-type uniform sampling algorithms over data streams are discussed in [12]. A parallel uniform random sampling algorithm is given in [10]. In weighted random sampling (WRS) the items are weighted and the probability of each item to be selected is determined by its relative weight. WRS can be defined with the following algorithm D:

Algorithm D, a definition of WRS

Input::

A population V of n weighted items

Output::

A set S with a WRS of size m

1::

For ${ k=1 }$ to m do

2::

Let ${ p_i(k) {\,=\,} {w_i}/{\sum_{s_j \in V-S} w_j} }$ be the probability of item v _i to be selected in round k

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