Weighted Reservoir Sampling with Replacement from Data Streams
Abstract
In this work, we present a new random sampling method for data streams where the probability of an element's inclusion in the sample is proportional to a weight associated with that element. Our method is based on sampling with replacement, although most of the literature on this topic has focused on sampling without replacement.
Fields of Study & Subjects
Reservoir Engineering and Simulation Methods
Seismic Imaging and Inversion Techniques
Data Stream Mining Techniques
Publication details
- Journal / source
- Proceedings of the ACM Web Conference 2026
- Publisher
- ACM
- Pages
- 8789–8792
- Publication date
- 9 April 2026