On the public citation graph

ADARC: An anomaly detection algorithm based on relative outlier distance and biseries correlation

https://doi.org/10.1002/spe.2756
0 signed · 66 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1007/11430919_92openalex-snapshot
An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning
inferredcites →https://doi.org/10.1007/978-1-4899-7993-3_80719-1openalex-snapshot
Outlier Detection
inferredcites →https://doi.org/10.1007/978-3-319-19665-7_29openalex-snapshot
Democratic Tone Mapping Using Optimal K-means Clustering
inferredcites →https://doi.org/10.1007/978-3-642-00202-1_24openalex-snapshot
The Planar k-Means Problem is NP-Hard
inferredcites →https://doi.org/10.1007/978-3-662-56707-4_9openalex-snapshot
Cluster Analysis
inferredcites →https://doi.org/10.1007/s007780050006openalex-snapshot
Distance-based outliers: algorithms and applications
inferredcites →https://doi.org/10.1007/s00779-014-0786-zopenalex-snapshot
An extensible and active semantic model of information organizing for the Internet of Things
inferredcites →https://doi.org/10.1007/s10994-009-5103-0openalex-snapshot
NP-hardness of Euclidean sum-of-squares clustering
inferredcites →https://doi.org/10.1016/0098-3004(84)90020-7openalex-snapshot
FCM: The fuzzy c-means clustering algorithm
inferredcites →https://doi.org/10.1016/j.asoc.2019.02.032openalex-snapshot
An evolving recurrent interval type-2 intuitionistic fuzzy neural network for online learning and time series prediction
inferredcites →https://doi.org/10.1016/j.comnet.2018.11.031openalex-snapshot
A fast shapelet selection algorithm for time series classification
inferredcites →https://doi.org/10.1016/j.comnet.2019.04.020openalex-snapshot
A just-in-time shapelet selection service for online time series classification
inferredcites →https://doi.org/10.1016/j.engappai.2010.09.007openalex-snapshot
A review on time series data mining
inferredcites →https://doi.org/10.1016/j.eswa.2008.01.039openalex-snapshot
A simple and fast algorithm for K-medoids clustering
inferredcites →https://doi.org/10.1016/j.ins.2015.04.018openalex-snapshot
Predefined pattern detection in large time series
inferredcites →https://doi.org/10.1016/j.neucom.2017.08.026openalex-snapshot
Hierarchical Temporal Memory method for time-series-based anomaly detection
inferredcites →https://doi.org/10.1016/j.physa.2017.01.008openalex-snapshot
A grouping method based on grid density and relationship for crowd evacuation simulation
inferredcites →https://doi.org/10.1016/j.procs.2018.03.025openalex-snapshot
A Shapelet Selection Algorithm for Time Series Classification: New Directions
inferredcites →https://doi.org/10.1080/01969727308546046openalex-snapshot
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
inferredcites →https://doi.org/10.1080/14786440109462720openalex-snapshot
LIII. On lines and planes of closest fit to systems of points in space
inferredcites →https://doi.org/10.1108/jstpm-02-2018-0020openalex-snapshot
Rescaling and refocusing smart cities research: from mega cities to smart villages
inferredcites →https://doi.org/10.1109/ascc.2015.7244794openalex-snapshot
A support vector machine based technique for online detection of outliers in transient time series
inferredcites →https://doi.org/10.1109/fskd.2016.7603383openalex-snapshot
Improved abnormality detection from raw ECG signals using feature enhancement
inferredcites →https://doi.org/10.1109/icaci.2015.7184758openalex-snapshot
Brain storm optimization algorithms with k-medians clustering algorithms
inferredcites →https://doi.org/10.1109/icdm.2007.12openalex-snapshot
Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors
inferredcites →https://doi.org/10.1109/icdm.2008.151openalex-snapshot
Comparative Evaluation of Anomaly Detection Techniques for Sequence Data
inferredcites →https://doi.org/10.1109/icdmw.2015.104openalex-snapshot
Large-Scale Unusual Time Series Detection
inferredcites →https://doi.org/10.1109/ifsa-nafips.2013.6608627openalex-snapshot
Anomaly detection in time series data using a fuzzy c-means clustering
inferredcites →https://doi.org/10.1109/sii.2017.8279219openalex-snapshot
Adjacent Mean Difference (AMD) method for dynamic segmentation in time series anomaly detection
inferredcites →https://doi.org/10.1109/tfuzz.2014.2302456openalex-snapshot
Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach
inferredcites →https://doi.org/10.1109/tit.1982.1056489openalex-snapshot
Least squares quantization in PCM
inferredcites →https://doi.org/10.1109/tit.2009.2021326openalex-snapshot
Random Projection Trees for Vector Quantization
inferredcites →https://doi.org/10.1109/tkde.2006.1599387openalex-snapshot
A unifying framework for detecting outliers and change points from time series
inferredcites →https://doi.org/10.1109/tkde.2010.235openalex-snapshot
Anomaly Detection for Discrete Sequences: A Survey
inferredcites →https://doi.org/10.1109/tmech.2006.878544openalex-snapshot
Symbolic time-series analysis for anomaly detection in mechanical systems
inferredcites →https://doi.org/10.1109/tnn.2005.845141openalex-snapshot
Survey of Clustering Algorithms
inferredcites →https://doi.org/10.1111/j.1365-2966.2006.10327.xopenalex-snapshot
Finding outlier light curves in catalogues of periodic variable stars
inferredcites →https://doi.org/10.1137/1.9781611972757.40openalex-snapshot
On Periodicity Detection and Structural Periodic Similarity
inferredcites →https://doi.org/10.1145/1014052.1014077openalex-snapshot
Towards parameter-free data mining
inferredcites →https://doi.org/10.1145/2379776.2379788openalex-snapshot
Time-series data mining
inferredcites →https://doi.org/10.1145/2395116.2395117openalex-snapshot
The effectiveness of lloyd-type methods for the k-means problem
inferredcites →https://doi.org/10.1145/2783258.2788611openalex-snapshot
Generic and Scalable Framework for Automated Time-series Anomaly Detection
inferredcites →https://doi.org/10.1145/775047.775128openalex-snapshot
Finding surprising patterns in a time series database in linear time and space
inferredcites →https://doi.org/10.1155/2014/517486openalex-snapshot
Constructing the Web of Events from Raw Data in the Web of Things
inferredcites →https://doi.org/10.2307/1912100openalex-snapshot
Time Series Analysis Forecasting and Control
inferredcites →https://doi.org/10.2307/2003798openalex-snapshot
Theory of the Motion of the Heavenly Bodies Moving about the Sun in Conic Sections
inferredcites →https://doi.org/10.2307/2346830openalex-snapshot
Algorithm AS 136: A K-Means Clustering Algorithm
inferredcites →https://doi.org/10.32614/rj-2011-015openalex-snapshot
Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming
inferredcites →https://doi.org/10.3390/s16030279openalex-snapshot
Device Data Ingestion for Industrial Big Data Platforms with a Case Study
inferredcites →https://doi.org/10.3390/su10061998openalex-snapshot
Who Uses Smart City Services and What to Make of It: Toward Interdisciplinary Smart Cities Research
inferredcites →https://doi.org/10.4018/ijwsr.2017040104openalex-snapshot
A Fast Shapelet Discovery Algorithm Based on Important Data Points

What points at this work

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

inferred← citeshttps://doi.org/10.1002/lom3.10449openalex-snapshot
Quantifying upwelling in tropical shallow waters: A novel method using a temperature stratification index
inferred← citeshttps://doi.org/10.1002/spe.2785openalex-snapshot
Standalone noise and anomaly detection in wireless sensor networks: A novel time‐series and adaptive Bayesian‐network‐based approach
inferred← citeshttps://doi.org/10.1002/spe.3052openalex-snapshot
Dynamics signature based anomaly detection
inferred← citeshttps://doi.org/10.1007/978-981-16-2540-4_23openalex-snapshot
Cooperative Anomaly Detection Model and Real-Time Update Strategy for Industrial Stream Data
inferred← citeshttps://doi.org/10.1007/978-981-19-5209-8_22openalex-snapshot
M-ISFCM: A Semisupervised Method for Anomaly Detection of MOOC Learning Behavior
inferred← citeshttps://doi.org/10.1007/s00521-019-04685-wopenalex-snapshot
Multimodality registration for ocular multispectral images via co-embedding
inferred← citeshttps://doi.org/10.1007/s00521-020-05432-2openalex-snapshot
Fault detection of continuous glucose measurements based on modified k-medoids clustering algorithm
inferred← citeshttps://doi.org/10.1016/j.ins.2021.08.097openalex-snapshot
An efficient anomaly detection method for uncertain data based on minimal rare patterns with the consideration of anti-monotonic constraints
inferred← citeshttps://doi.org/10.1016/j.jksuci.2023.101783openalex-snapshot
Time series classification with random temporal features
inferred← citeshttps://doi.org/10.1063/5.0239052openalex-snapshot
Predictive patterns: Unveiling market trends with n-gram candlestick mining
inferred← citeshttps://doi.org/10.1109/access.2020.2982662openalex-snapshot
An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features
inferred← citeshttps://doi.org/10.1109/access.2024.3361672openalex-snapshot
Indicator Fault Detection Method Based on Periodic Self Discovery and Historical Anomaly Filtering
inferred← citeshttps://doi.org/10.1109/ddcls52934.2021.9455470openalex-snapshot
Anomaly detection method based on multi-criteria evaluation for energy data of steel industry
inferred← citeshttps://doi.org/10.3390/e21121187openalex-snapshot
The Entropy-Based Time Domain Feature Extraction for Online Concept Drift Detection
inferred← citeshttps://doi.org/10.5784/39-1-711openalex-snapshot
Anomaly detection using autoencoders with network analysis features
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.