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Time series data cleaning

https://doi.org/10.14778/3115404.3115410
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9780470316436openalex-snapshot
Linear Statistical Inference and its Applications
inferredcites →https://doi.org/10.1002/9781118445112.stat05549openalex-snapshot
Y ule– W alker Equations
inferredcites →https://doi.org/10.1002/for.3980070102openalex-snapshot
Outliers, level shifts, and variance changes in time series
inferredcites →https://doi.org/10.1007/978-3-319-29854-2openalex-snapshot
Introduction to Time Series and Forecasting
inferredcites →https://doi.org/10.1007/b97391openalex-snapshot
Introduction to Time Series and Forecasting
inferredcites →https://doi.org/10.1007/s10115-011-0400-xopenalex-snapshot
Early classification on time series
inferredcites →https://doi.org/10.1016/j.envsoft.2009.08.010openalex-snapshot
Anomaly detection in streaming environmental sensor data: A data-driven modeling approach
inferredcites →https://doi.org/10.1016/j.ijforecast.2006.03.005openalex-snapshot
Exponential smoothing: The state of the art—Part II
inferredcites →https://doi.org/10.1016/j.jsv.2004.10.013openalex-snapshot
An outlier analysis framework for impedance-based structural health monitoring
inferredcites →https://doi.org/10.1080/01621459.1975.10480264openalex-snapshot
Intervention Analysis with Applications to Economic and Environmental Problems
inferredcites →https://doi.org/10.1109/icde.2013.6544847openalex-snapshot
Holistic data cleaning: Putting violations into context
inferredcites →https://doi.org/10.1109/icde.2014.6816655openalex-snapshot
Continuous data cleaning
inferredcites →https://doi.org/10.1111/j.1467-9892.2009.00643.xopenalex-snapshot
Time series analysis forecasting and control
inferredcites →https://doi.org/10.1137/1.9780898719246openalex-snapshot
Time Series
inferredcites →https://doi.org/10.1145/1066157.1066175openalex-snapshot
A cost-based model and effective heuristic for repairing constraints by value modification
inferredcites →https://doi.org/10.1145/1150402.1150485openalex-snapshot
Algorithms for time series knowledge mining
inferredcites →https://doi.org/10.1145/2487575.2488188openalex-snapshot
U-Air
inferredcites →https://doi.org/10.1145/2723372.2723730openalex-snapshot
SCREEN
inferredcites →https://doi.org/10.1145/2783258.2783317openalex-snapshot
Turn Waste into Wealth
inferredcites →https://doi.org/10.1145/775047.775148openalex-snapshot
A unifying framework for detecting outliers and change points from non-stationary time series data
inferredcites →https://doi.org/10.14778/1920841.1920867openalex-snapshot
Towards certain fixes with editing rules and master data
inferredcites →https://doi.org/10.14778/2535568.2448943openalex-snapshot
Truth finding on the deep web
inferredcites →https://doi.org/10.1787/9789264244047-52-enopenalex-snapshot
United Nations Economic Commission for Europe (UNECE)
inferredcites →https://doi.org/10.2200/s00573ed1v01y201403dmk008openalex-snapshot
Outlier Detection for Temporal Data
inferredcites →https://doi.org/10.2307/2285347openalex-snapshot
Time Series: Data Analysis and Theory.
inferredcites →https://doi.org/10.2307/2965440openalex-snapshot
Introduction to Time Series and Forecasting.
inferredcites →https://doi.org/10.2307/2988198openalex-snapshot
Time Series Analysis: Forecasting and Control.
inferredcites →https://doi.org/10.5555/1182635.1164143openalex-snapshot
Adaptive cleaning for RFID data streams
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques
inferredcites →https://doi.org/10.7551/mitpress/2946.001.0001openalex-snapshot
Extrapolation, Interpolation, and Smoothing of Stationary Time Series

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Threshold Functional Dependencies for Time Series Data
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Time Series Data Cleaning Based on Dynamic Speed Constraints
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Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
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Novelets: a new primitive that allows online detection of emerging behaviors in time series
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AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series
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Fuzz Testing Molecular Representation Using Deep Variational Anomaly Generation
inferred← citeshttps://doi.org/10.1088/1361-6501/ade611openalex-snapshot
Time series data cleaning based on sliding window and linear fitting method for vibrating wire strain gauges
inferred← citeshttps://doi.org/10.1089/big.2018.0148openalex-snapshot
Abnormal Data Region Discrimination and Cross-Monitoring Points Historical Correlation Repair of Water Intake Data
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Progress in Outlier Detection Techniques: A Survey
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Time Series Data Cleaning: A Survey
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A Survey of Approximate Quantile Computation on Large-Scale Data
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Analysis of Time Series Data Generated From the Internet of Things Using Deep Learning Models
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Will my Flight be on Time? Learning from Part Failures to Predict Future Reliability
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SDCCD: Spatiotemporal Data Cleaning based on Collision Detection
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TsRss: A Practical Stream data Cleaning Method based on Local Shape Feature
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Time Series Forecasting in a CVD Reactor for Polysilicon Production
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A Laser-based Volumetric Measurement Approach for Industrial Settings
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Data Quality Visual Analysis (DQVA) A tool to process and pinspot raw data irregularities
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CARMUS: Towards a General Framework for Continuous Activity Recognition with Missing Values on Smartphones
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Knowledge Fusion and Spatiotemporal Data Cleaning: A Review
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The Concept of Detecting and Classifying Anomalies in Large Data Sets on a Basis of Information Granules
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VADETIS: An Explainable Evaluator for Anomaly Detection Techniques
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TSDDISCOVER: Discovering Data Dependency for Time Series Data
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Time Series Data Cleaning Under Expressive Constraints on Both Rows and Columns
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MINOR: Multivariate Time Series Iterative Cleaning Algorithm
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Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning
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Predicting stock market indexes with world news
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ORBITS
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Stream Data Cleaning for Dynamic Line Rating Application
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Application of Deep Learning in Drainage Systems Monitoring Data Repair—A Case Study Using Con-GRU Model
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Efficient Join Processing Over Incomplete Data Streams (Technical Report)
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Skyline Queries Over Incomplete Data Streams (Technical Report)
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Time Series Data Cleaning with Regular and Irregular Time Intervals
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A Survey on Sampling and Profiling over Big Data (Technical Report)
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AutoML to Date and Beyond: Challenges and Opportunities
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Online Topic-Aware Entity Resolution Over Incomplete Data Streams (Technical Report)
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Interoperation mechanism for Industrial internet of things. Applications and smart city
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FedLGAN: a method for anomaly detection and repair of hydrological telemetry data based on federated learning
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