Partitioning and Ranking Tagged Data Sources

Summary: Introduces tag-centric algorithms that jointly organize socially generated content by partitioning the full tag collection under specified constraints and rapidly ranking selected partitions. Experiments on the complete Twitter firehose demonstrate scalability and practical utility. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 10877
Venue: VLDB
Year: 2013
Pagerank: 5.7510417e-05
Overall Rank: 6,864 | 52.91%
DOI: 10.14778/2535570.2488330

Incoming Non-self Citations Over Time

Authors

1. Milad Eftekhar (University of Toronto)
2. Nick Koudas (University of Toronto)

BibTeX Citation

@article{eftekhar_vldb13,
        title = {{Partitioning and Ranking Tagged Data Sources}},
        author = {Eftekhar, Milad and Koudas, Nick},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {4},
        doi = {10.14778/2535570.2488330},
        url = {https://doi.org/10.14778/2535570.2488330},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,501	Tracking Set Correlations at Large Scale	2014	SIGMOD	5.2592462e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
4,855	Structural Trend Analysis for Online Social Networks	2011	VLDB	6.4766126e-05
7,834	Identifying, Attributing and Describing Spatial Bursts	2010	VLDB	5.535728e-05
12,546	Improved Search for Socially Annotated Data	2009	VLDB	5.093636e-05

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