SOTAVerified

Time Series Clustering

Time Series Clustering is an unsupervised data mining technique for organizing data points into groups based on their similarity. The objective is to maximize data similarity within clusters and minimize it across clusters. Time-series clustering is often used as a subroutine of other more complex algorithms and is employed as a standard tool in data science for anomaly detection, character recognition, pattern discovery, visualization of time series.

Source: Comprehensive Process Drift Detection with Visual Analytics

Papers

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Showing 1–50 of 113 papers

TitleStatusHype
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time SeriesCode2
Temporal Phenotyping using Deep Predictive Clustering of Disease ProgressionCode1
Novel Features for Time Series Analysis: A Complex Networks ApproachCode1
Smart Data Collection System for Brownfield CNC Milling Machines: A New Benchmark Dataset for Data-Driven Machine MonitoringCode1
Graph-based Time Series Clustering for End-to-End Hierarchical ForecastingCode1
k-Graph: A Graph Embedding for Interpretable Time Series ClusteringCode1
Latent Space Semi-Supervised Time Series Data Clustering—0
A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers—0
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale—0
Interpretable Spectral Variational AutoEncoder (ISVAE) for time series clustering—0
A self-organising eigenspace map for time series clustering—0
A system identification approach to clustering vector autoregressive time series—0
4TaStiC: Time and trend traveling time series clustering for classifying long-term type 2 diabetes patients—0
Autoencoder-based time series clustering with energy applications—0
Approximate Collapsed Gibbs Clustering with Expectation Propagation—0
Interpretable Time Series Clustering Using Local Explanations—0
Actor-Critic Approach for Temporal Predictive Clustering—0
Bridging the Gap: A Decade Review of Time-Series Clustering Methods—0
Clustering Macroeconomic Time Series—0
Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology—0
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy—0
Clustering of Urban Traffic Patterns by K-Means and Dynamic Time Warping: Case Study—0
Clustering piecewise stationary processes—0
Clustering Time-Series by a Novel Slope-Based Similarity Measure Considering Particle Swarm Optimization—0
Clustering Time Series Data with Gaussian Mixture Embeddings in a Graph Autoencoder Framework—0
Concrete Dense Network for Long-Sequence Time Series Clustering—0
Analysis of Hydrological and Suspended Sediment Events from Mad River Watershed using Multivariate Time Series Clustering—0
Coresets for Time Series Clustering—0
Identifying the module structure of swarms using a new framework of network-based time series clustering—0
Kernel Spectral Clustering and applications—0
Detecting CAN Masquerade Attacks with Signal Clustering Similarity—0
Deep Temporal Contrastive Clustering—0
AUTOSHAPE: An Autoencoder-Shapelet Approach for Time Series Clustering—0
A Benchmark Study on Time Series Clustering—0
Determining the Optimal Number of Clusters for Time Series Datasets with Symbolic Pattern Forest—0
Diffeomorphic Transformations for Time Series Analysis: An Efficient Approach to Nonlinear Warping—0
Clustering evolving data using kernel-based methods—0
Discovering Playing Patterns: Time Series Clustering of Free-To-Play Game Data—0
Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering—0
Dynamic clustering of time series data—0
Early Predictions for Medical Crowdfunding: A Deep Learning Approach Using Diverse Inputs—0
Evaluation of k-means time series clustering based on z-normalization and NP-Free—0
Examining the Dynamics of Local and Transfer Passenger Share Patterns in Air Transportation—0
A Review and Evaluation of Elastic Distance Functions for Time Series Clustering—0
Fuzzy clustering of circular time series based on a new dependence measure with applications to wind data—0
Fuzzy clustering of ordinal time series based on two novel distances with economic applications—0
Granger Causality Based Hierarchical Time Series Clustering for State Estimation—0
An Empirical Evaluation of Similarity Measures for Time Series Classification—0
Hierarchical Clustering using Auto-encoded Compact Representation for Time-series Analysis—0
Hydroclimatic time series features at multiple time scales—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SOM-VAE-probNMI (physiology_6_hours)0.05—Unverified
2k-meansNMI (physiology_6_hours)0.04—Unverified
3SOM-VAENMI (physiology_6_hours)0.04—Unverified