MAIDS: Mining Alarming Incidents from Data Streams

Summary: MAIDS enables alarming-incident mining on data streams with tilted time windows for multi-resolution modeling and a stream data cube for online multi-dimensional analysis. Online classification, frequent-pattern mining, clustering, and visualization for instant anomaly detection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h663a2e878689c75b
Venue: SIGMOD
Year: 2004
Pagerank: 5.1562553e-05
Overall Rank: 9,484 | 36.43%
DOI: 10.1145/1007568.1007695

Incoming Non-self Citations Over Time

Authors

1. Y. Dora Cai (University of Illinois Urbana-Champaign)
2. David Clutter (University of Illinois Urbana-Champaign)
3. Greg Pape (University of Illinois Urbana-Champaign)
4. Jiawei Han (University of Illinois Urbana-Champaign)
5. Michael Welge (University of Illinois Urbana-Champaign)
6. Loretta Auvil (University of Illinois Urbana-Champaign)

BibTeX Citation

@inproceedings{cai_sigmod04,
        title = {{MAIDS: Mining Alarming Incidents from Data Streams}},
        author = {Cai, Y. Dora and Clutter, David and Pape, Greg and Han, Jiawei and Welge, Michael and Auvil, Loretta},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007695},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007695},
        year = {2004}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,553	Effective Variation Management for Pseudo Periodical Streams	2007	SIGMOD	5.48019e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 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	0.00051942573
32	BIRCH: An Efficient Data Clustering Method for Very Large Databases	1996	SIGMOD	0.00049559562
165	Mining Frequent Patterns without Candidate Generation	2000	SIGMOD	0.00027323925
364	CURE: An Efficient Clustering Algorithm for Large Databases	1998	SIGMOD	0.00019916561
933	A Framework for Clustering Evolving Data Streams	2003	VLDB	0.00012976795
1,883	Efficient Computation of Iceberg Cubes with Complex Measures	2001	SIGMOD	9.4237043e-05
2,222	Multi-Dimensional Regression Analysis of Time-Series Data Streams	2002	VLDB	8.8048988e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	13,115	Indexing and Mining Streams	2004	SIGMOD
2	911	Finding Frequent Items in Data Streams	2008	VLDB
3	3,950	Continuous Outlier Detection in Data Streams: An Extensible Framework and State-Of-The-Art Algorithms	2013	SIGMOD
4	1,295	Querying and Mining Data Streams: You Only Get One Look	2002	SIGMOD
5	9,485	A Framework for Projected Clustering of High Dimensional Data Streams	2004	VLDB
6	13,124	StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams	2004	VLDB
7	8,898	Interactive Visual Exploration of Neighbor-Based Patterns in Data Streams	2010	SIGMOD
8	933	A Framework for Clustering Evolving Data Streams	2003	VLDB
9	12,615	Mining and Linking Patterns across Live Data Streams and Stream Archives	2013	VLDB
10	2,222	Multi-Dimensional Regression Analysis of Time-Series Data Streams	2002	VLDB