DBScholar

Back to papers

PODS: A New Model and Processing Algorithms for Uncertain Data Streams

Summary: Uncertain data streams modeled with continuous random variables; PODS offers a flexible data model enabling efficient evaluation of aggregates and joins. Statistics-based approximation delivers strong accuracy and high performance, outperforming sampling, with a tornado-detection case study at stream speed. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4303
Venue
SIGMOD
Year
2010
Pagerank
5.9949334e-05
Overall Rank
6,049 | 58.50%
DOI
10.1145/1807167.1807187

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{tran_sigmod10,
        title = {{PODS: A New Model and Processing Algorithms for Uncertain Data Streams}},
        author = {Tran, Thanh T. L. and Peng, Liping and Li, Boduo and Diao, Yanlei and Liu, Anna},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807187},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807187},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers