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Information Theory For Data Management

Summary: Tutorial on applying entropy, KL-divergence, conditional entropy, and mutual information to data representation and analysis. Connects these measures to information content, signal strength, complexity, and redundancy, while addressing efficient computation. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10175
Venue
VLDB
Year
2009
Pagerank
5.093636e-05
Overall Rank
12,548 | 13.91%
DOI
10.14778/1687553.1687624

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@article{srivastava_vldb09,
        title = {{Information Theory For Data Management}},
        author = {Srivastava, Divesh and Venkatasubramanian, Suresh},
        journal = {PVLDB},
        series = {{VLDB} '09},
        doi = {10.14778/1687553.1687624},
        url = {https://doi.org/10.14778/1687553.1687624},
        year = {2009}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
955 Truth Finding on the Deep Web: Is the Problem Solved? 2013 VLDB 0.00012996675
12,183 Online Ordering of Overlapping Data Sources 2014 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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