Efficient Discovery of Sequence Outlier Patterns

Summary: TOP detects contextual outlier patterns by separating independent occurrences from those inside super-patterns in IoT sequences. A top-down Reduce strategy with context pruning and inverted indexing yields linear-time mining and fast speedups over bottom-up methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12015
Venue: VLDB
Year: 2019
Pagerank: 4.5814937e-05
Overall Rank: 8,117 | 43.54%
DOI: 10.14778/3324301.3324308

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,157	TOD: GPU-accelerated Outlier Detection via Tensor Operations	2023	VLDB	4.5730908e-05
11,039	Efficient Discovery of Significant Patterns with Few-Shot Resampling	2024	VLDB	4.1945683e-05

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
362	Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases	1995	VLDB	0.00025770385
5,182	Active Complex Event Processing over Event Streams	2011	VLDB	5.6410216e-05

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