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Detecting Change in Data Streams

Summary: Novel, distribution-free change detection and estimation for data streams under independence. Provides statistical guarantees, descriptive quantification of changes, and applicability to both discrete and continuous data, with empirical validation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9214
Venue
VLDB
Year
2004
Pagerank
6.8448674e-05
Overall Rank
3,685 | 74.37%
DOI
-

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Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
43 Models and Issues in Data Stream Systems 2002 PODS 0.00072723062
662 A Framework for Clustering Evolving Data Streams 2003 VLDB 0.00018475968
728 Meaningful Change Detection in Structured Data 1997 SIGMOD 0.00017494982
3,894 Mining surprising patterns using temporal description length 1998 VLDB 6.6583221e-05
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