Lahar Demonstration: Warehousing Markovian Streams

Summary: Lahar warehouses Markovian, probabilistically inferred streams from sources such as speech, GPS, and sensors, enabling OLAP over uncertain archives. It combines approximation and indexing techniques for efficient probability-aware queries, demonstrated on podcast-derived text streams. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 10111
Venue: VLDB
Year: 2009
Pagerank: -
Overall Rank: 13,746 | 5.69%
DOI: 10.14778/1687553.1687605

Incoming Non-self Citations Over Time

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

Authors

1. Julie Letchner (University of Washington)
2. Christopher Ré (University of Washington)
3. Magdalena Balazinska (University of Washington)
4. Matthai Philipose (Intel Research Seattle)

BibTeX Citation

@article{letchner_vldb09,
        title = {{Lahar Demonstration: Warehousing Markovian Streams}},
        author = {Letchner, Julie and Ré, Christopher and Balazinska, Magdalena and Philipose, Matthai},
        journal = {PVLDB},
        series = {{VLDB} '09},
        doi = {10.14778/1687553.1687605},
        url = {https://doi.org/10.14778/1687553.1687605},
        year = {2009}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
12,408	Transducing Markov Sequences	2010	PODS	5.093636e-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
3,050	Event Queries on Correlated Probabilistic Streams	2008	SIGMOD	7.8140428e-05

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