A New Distributional Treatment for Time Series and An Anomaly Detection Investigation

Summary: R-domain time-series: subsequences treated as iid samples from an unknown distribution in R, enabling distributional similarity (WD, KME, IDK) and removing sliding windows. IDK-based detectors offer improved accuracy over sliding-window methods with linear-time performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12725
Venue: VLDB
Year: 2022
Pagerank: 4.5903492e-05
Overall Rank: 8,083 | 43.77%
DOI: 10.14778/3551793.3551796

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,777	ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection	2024	VLDB	5.3308813e-05
6,440	An Experimental Evaluation of Anomaly Detection in Time Series	2024	VLDB	5.0603878e-05

Outgoing Citations (Sorted by Pagerank)

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
161	LOF: Identifying Density-Based Local Outliers	2000	SIGMOD	0.00039846974
774	Algorithms for Mining Distance-Based Outliers in Large Datasets	1998	VLDB	0.00016865771
1,516	k-Shape: Efficient and Accurate Clustering of Time Series	2015	SIGMOD	0.00011586255
4,853	Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures	2020	SIGMOD	5.8760276e-05

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7,182	TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms	2022	VLDB	4.8072409e-05
1,161	Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures	2008	VLDB	0.00013585236
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10,466	A Structured Study of Multivariate Time-Series Distance Measures	2025	SIGMOD	4.1945683e-05
11,094	Time-Series Anomaly Detection: Overview and New Trends	2024	VLDB	4.1945683e-05
4,853	Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures	2020	SIGMOD	5.8760276e-05
1,253	Anomaly Detection in Time Series: A Comprehensive Evaluation	2022	VLDB	0.00013032074
6,440	An Experimental Evaluation of Anomaly Detection in Time Series	2024	VLDB	5.0603878e-05