Exceeding Expectations and Clustering Uncertain Data

Summary: True approximation algorithms for k‑center clustering on probabilistic/uncertain data that preserve the number of centers, closing gaps in prior work. Introduce an "exceeding expectations" objective (contribution above expectation) and general optimization techniques under uncertainty. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: hdf5ce87b59a50d57
Venue: PODS
Year: 2009
Pagerank: 5.6363458e-05
Overall Rank: 6,950 | 53.28%
DOI: 10.1145/1559795.1559836

Incoming Non-self Citations Over Time

Authors

1. Sudipto Guha (University of Pennsylvania)
2. Kamesh Munagala (Duke University)

BibTeX Citation

@inproceedings{guha_pods09,
        address = {New York, NY, USA},
        series = {{PODS} '09},
        title = {{Exceeding Expectations and Clustering Uncertain Data}},
        url = {https://dl.acm.org/doi/10.1145/1559795.1559836},
        doi = {10.1145/1559795.1559836},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Guha, Sudipto and Munagala, Kamesh},
        year = {2009}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,904	Improvements on the k-center Problem for Uncertain Data	2018	PODS	5.2559789e-05
12,795	Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary)	2009	SIGMOD	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
2,304	Approximation Algorithms for Clustering Uncertain Data	2008	PODS	8.6702799e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	5,656	Uncertainty Aware Query Execution Time Prediction	2014	VLDB
2	690	Creating Probabilistic Databases from Information Extraction Models	2006	VLDB
3	370	Evaluating Probabilistic Queries over Imprecise Data	2003	SIGMOD
4	7,114	Uncertain Centroid based Partitional Clustering of Uncertain Data	2012	VLDB
5	8,904	Improvements on the k-center Problem for Uncertain Data	2018	PODS
6	9,050	Stochastic Package Queries in Probabilistic Databases	2020	SIGMOD
7	12,795	Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary)	2009	SIGMOD
8	6,475	Clustering Uncertain Graphs	2018	VLDB
9	12,758	Conditioning and Aggregating Uncertain Data Streams: Going Beyond Expectations	2010	VLDB
10	2,304	Approximation Algorithms for Clustering Uncertain Data	2008	PODS