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Interactive Visual Exploration of Neighbor-Based Patterns in Data Streams

Summary: ViStream: interactive visual exploration of neighbor-based patterns in streams. A shared multi-query execution strategy for real-time pattern mining (clusters, outliers) plus a visualization layer enabling dynamic parameter tuning across time horizons. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4398
Venue
SIGMOD
Year
2010
Pagerank
5.3809865e-05
Overall Rank
8,704 | 40.29%
DOI
10.1145/1807167.1807305

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yang_sigmod10,
        title = {{Interactive Visual Exploration of Neighbor-Based Patterns in Data Streams}},
        author = {Yang, Di and Guo, Zhenyu and Xie, Zaixian and Rundensteiner, Elke and Ward, Matthew},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807305},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807305},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
907 A Framework for Clustering Evolving Data Streams 2003 VLDB 0.00013309819
7,695 A Shared Execution Strategy for Multiple Pattern Mining Requests over Streaming Data 2009 VLDB 5.5661355e-05
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