A Framework for Projected Clustering of High Dimensional Data Streams

Summary: HPStream brings projected clustering to high-dimensional streams via an incrementally updatable, fading-cluster structure. It enables single-pass, scalable processing across dimensions and stream volume while improving clustering quality over prior stream methods. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 9383
Venue: VLDB
Year: 2004
Pagerank: 5.2945481e-05
Overall Rank: 9,272 | 36.39%
DOI: 10.1016/B978-012088469-8.50075-9

Incoming Non-self Citations Over Time

Authors

1. Charu C. Aggarwal (IBM)
2. Jiawei Han (University of Illinois Urbana-Champaign)
3. Jianyong Wang (University of Illinois Urbana-Champaign; University of Minnesota at Twin Cities)
4. Philip S. Yu (IBM)

BibTeX Citation

@article{aggarwal_vldb04,
        title = {{A Framework for Projected Clustering of High Dimensional Data Streams}},
        author = {Aggarwal, Charu C. and Han, Jiawei and Wang, Jianyong and Yu, Philip S.},
        journal = {PVLDB},
        series = {{VLDB} '04},
        pages = {852},
        doi = {10.1016/B978-012088469-8.50075-9},
        url = {https://doi.org/10.1016/B978-012088469-8.50075-9},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,229	On Biased Reservoir Sampling in the Presence of Stream Evolution	2006	VLDB	6.8181027e-05
7,400	Effective Variation Management for Pseudo Periodical Streams	2007	SIGMOD	5.6255397e-05
8,081	Challenges and Experience in Prototyping a Multi-Modal Stream Analytic and Monitoring Application on System S	2007	VLDB	5.4921185e-05

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
26	Models and Issues in Data Stream Systems	2002	PODS	0.00052982574
31	BIRCH: An Efficient Data Clustering Method for Very Large Databases	1996	SIGMOD	0.00050347119
88	Efficient and Effective Clustering Methods for Spatial Data Mining	1994	VLDB	0.00035240327
291	OPTICS: Ordering Points To Identify the Clustering Structure	1999	SIGMOD	0.00022264197
304	Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications	1998	SIGMOD	0.00021917388
351	CURE: An Efficient Clustering Algorithm for Large Databases	1998	SIGMOD	0.00020424271
907	A Framework for Clustering Evolving Data Streams	2003	VLDB	0.00013309819
1,646	Fast Algorithms for Projected Clustering	1999	SIGMOD	0.00010128564
6,750	A Framework for Diagnosing Changes in Evolving Data Streams	2003	SIGMOD	5.7842742e-05

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