Time Series Data Mining: A Unifying View
Summary: Demonstrates that a compact set of representations, distance measures, and primitives can solve most core time-series tasks (classification, clustering, joins, anomaly/motif discovery, summarization). Unifying tutorial with cross-domain examples and openly released datasets/code for reproducible analysis. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Eamonn Keogh
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,467 | TD-Join: Leveraging Temporal Dependencies in Time Series Joins | 2025 | SIGMOD | 4.1905499e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,253 | Anomaly Detection in Time Series: A Comprehensive Evaluation | 2022 | VLDB | 0.00013019488 |
| 4,258 | Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes | 2017 | VLDB | 6.3041152e-05 |
| 4,628 | Sim-Piece: Highly Accurate Piecewise Linear Approximation through Similar Segment Merging | 2023 | VLDB | 6.0321252e-05 |
| 5,248 | Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees | 2022 | VLDB | 5.6013482e-05 |
| 6,562 | SENSOR: Data-driven Construction of Sketch-based Visual Query Interfaces for Time Series Data | 2022 | VLDB | 5.0046642e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 12,284 | Parsimonious Linear Fingerprinting for Time Series | 2010 | VLDB | 4.1905499e-05 |
| 8,187 | FeatTS: Feature-based Time Series Clustering | 2021 | SIGMOD | 4.5606638e-05 |
| 12,086 | Mining and Linking Patterns across Live Data Streams and Stream Archives | 2013 | VLDB | 4.1905499e-05 |
| 10,888 | Representative Time Series Discovery for Data Exploration | 2025 | VLDB | 4.1905499e-05 |
| 8,226 | Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data | 2007 | VLDB | 4.5505782e-05 |
| 12,594 | Indexing and Mining Streams | 2004 | SIGMOD | 4.1905499e-05 |
| 11,097 | Time-Series Anomaly Detection: Overview and New Trends | 2024 | VLDB | 4.1905499e-05 |
| 10,746 | Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods | 2025 | VLDB | 4.1905499e-05 |
| 3,033 | A Decade of Progress in Indexing and Mining Large Time Series Databases | 2006 | VLDB | 7.6737668e-05 |
| 9,919 | Mining and Forecasting of Big Time-series Data | 2015 | SIGMOD | 4.2520778e-05 |