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Tracking Set Correlations at Large Scale

Summary: Continuous computation of correlations among co-occurring social-media tags in streaming data. Introduces tag-partitioning algorithms for scalable parallelization on a Storm cluster, minimizing tag replication and balancing load; validated with real-data experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4943
Venue
SIGMOD
Year
2014
Pagerank
5.2592462e-05
Overall Rank
9,501 | 34.82%
DOI
10.1145/2588555.2601050

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{alvanaki_sigmod14,
        title = {{Tracking Set Correlations at Large Scale}},
        author = {Alvanaki, Foteini and Michel, Sebastian},
        series = {{SIGMOD} '14},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2588555.2601050},
        url = {https://dl.acm.org/doi/10.1145/2588555.2601050},
        year = {2014}
}

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

Rank Cited Paper Year Venue Pagerank
1,439 TwitterMonitor: Trend Detection over the Twitter Stream 2010 SIGMOD 0.00010778916
6,864 Partitioning and Ranking Tagged Data Sources 2013 VLDB 5.7510417e-05
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