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Combining Databases and Signal Processing in Plato

Summary: Plato: an extensible DBMS that uses signal-processing to infer statistical models of spatiotemporal sensor measurements as noisy, incomplete samples of an underlying ground truth. Queries run over models (not raw readings), yielding strong compression, faster execution, and higher-quality results via explicit signal/noise separation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
268
Venue
CIDR
Year
2015
Pagerank
6.8325104e-05
Overall Rank
4,207 | 71.14%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{katsis_cidr15,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '15},
        title = {{Combining Databases and Signal Processing in Plato}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Katsis, Yannis and Freund, Yoav and Papakonstantinou, Yannis},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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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.

Rank Cited Paper Year Venue Pagerank
9 Online Aggregation 1997 SIGMOD 0.00077458002
106 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00033539462
337 Model-Driven Data Acquisition in Sensor Networks 2004 VLDB 0.00020783399
408 MauveDB: Supporting Model-based User Views in Database Systems 2006 SIGMOD 0.00019008806
1,437 Querying Continuous Functions in a Database System 2008 SIGMOD 0.00010790718
2,367 Using Probabilistic Models for Data Management in Acquisitional Environments 2005 CIDR 8.6855754e-05
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