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Clustering of nonstationary data streams: A survey of fuzzy partitional methods

https://doi.org/10.1002/widm.1258
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What this work says

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

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Two-Sample Test Statistics for Measuring Discrepancies Between Two Multivariate Probability Density Functions Using Kernel-Based Density Estimates
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Pattern Recognition with Fuzzy Objective Function Algorithms
inferredcites →https://doi.org/10.1007/978-3-319-52962-2_12openalex-snapshot
Graded Possibilistic Clustering of Non-stationary Data Streams
inferredcites →https://doi.org/10.1007/978-3-642-23783-6_17openalex-snapshot
Online Clustering of High-Dimensional Trajectories under Concept Drift
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Problems of Fuzzy c-Means Clustering and Similar Algorithms with High Dimensional Data Sets
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Clustering High-Dimensional Data
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Comparing Fuzzy Clusterings in High Dimensionality
inferredcites →https://doi.org/10.1007/bf02339490openalex-snapshot
Numerical taxonomy with fuzzy sets
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On Density-Based Data Streams Clustering Algorithms: A Survey
inferredcites →https://doi.org/10.1007/s41019-017-0048-yopenalex-snapshot
Tracking Time Evolving Data Streams for Short-Term Traffic Forecasting
inferredcites →https://doi.org/10.1007/s41066-015-0012-zopenalex-snapshot
DCC: a framework for dynamic granular clustering
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FCM: The fuzzy c-means clustering algorithm
inferredcites →https://doi.org/10.1016/b978-012722442-8/50016-1openalex-snapshot
A Framework for Clustering Evolving Data Streams
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Incremental clustering of dynamic data streams using connectivity based representative points
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A particle filter driven dynamic Gaussian mixture model approach for complex process monitoring and fault diagnosis
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Online fuzzy medoid based clustering algorithms
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Unsupervised possibilistic clustering
inferredcites →https://doi.org/10.1016/j.patcog.2006.06.021openalex-snapshot
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
inferredcites →https://doi.org/10.1016/j.patcog.2007.05.018openalex-snapshot
A survey of kernel and spectral methods for clustering
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Evolving Gustafson-kessel Possibilistic c-Means Clustering
inferredcites →https://doi.org/10.1080/00949659608811772openalex-snapshot
Stochastic versions of the em algorithm: an experimental study in the mixture case
inferredcites →https://doi.org/10.1080/01969727308546047openalex-snapshot
Cluster Validity with Fuzzy Sets
inferredcites →https://doi.org/10.1080/03610926.2015.1096388openalex-snapshot
Effects of drift and noise on the optimal sliding window size for data stream regression models
inferredcites →https://doi.org/10.1093/biomet/41.1-2.100openalex-snapshot
CONTINUOUS INSPECTION SCHEMES
inferredcites →https://doi.org/10.1093/biomet/89.2.359openalex-snapshot
Permutation tests for equality of distributions in high-dimensional settings
inferredcites →https://doi.org/10.1109/34.85677openalex-snapshot
A validity measure for fuzzy clustering
inferredcites →https://doi.org/10.1109/5.726788openalex-snapshot
Deterministic annealing for clustering, compression, classification, regression, and related optimization problems
inferredcites →https://doi.org/10.1109/91.227387openalex-snapshot
A possibilistic approach to clustering
inferredcites →https://doi.org/10.1109/91.413225openalex-snapshot
On cluster validity for the fuzzy c-means model
inferredcites →https://doi.org/10.1109/91.531779openalex-snapshot
The possibilistic C-means algorithm: insights and recommendations
inferredcites →https://doi.org/10.1109/91.531780openalex-snapshot
Comments on "A possibilistic approach to clustering"
inferredcites →https://doi.org/10.1109/cccm.2008.186openalex-snapshot
A Weighted Fuzzy Clustering Algorithm for Data Stream
inferredcites →https://doi.org/10.1109/fuzzy.2000.838654openalex-snapshot
Weighted possibilistic c-means clustering algorithms
inferredcites →https://doi.org/10.1109/fuzzy.2007.4295372openalex-snapshot
Single Pass Fuzzy C Means
inferredcites →https://doi.org/10.1109/iciecs.2009.5363379openalex-snapshot
rDenStream, A Clustering Algorithm over an Evolving Data Stream
inferredcites →https://doi.org/10.1109/icpr.2002.1047450openalex-snapshot
Data clustering using evidence accumulation
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A fuzzy c means variant for clustering evolving data streams
inferredcites →https://doi.org/10.1109/iraniancee.2012.6292449openalex-snapshot
Extending fuzzy c-means to clustering data streams
inferredcites →https://doi.org/10.1109/nafips.2008.4531233openalex-snapshot
Online fuzzy c means
inferredcites →https://doi.org/10.1109/soac.1990.82141openalex-snapshot
Incremental clustering for dynamic document databases
inferredcites →https://doi.org/10.1109/tfuzz.2003.809902openalex-snapshot
Fast accurate fuzzy clustering through data reduction
inferredcites →https://doi.org/10.1109/tfuzz.2006.876740openalex-snapshot
Soft transition from probabilistic to possibilistic fuzzy clustering
inferredcites →https://doi.org/10.1109/tfuzz.2010.2043440openalex-snapshot
Applying the Possibilistic c-Means Algorithm in Kernel-Induced Spaces
inferredcites →https://doi.org/10.1109/tfuzz.2014.2298244openalex-snapshot
Incremental Fuzzy Clustering With Multiple Medoids for Large Data
inferredcites →https://doi.org/10.1109/tkde.2002.1033770openalex-snapshot
CLARANS: a method for clustering objects for spatial data mining
inferredcites →https://doi.org/10.1109/tkde.2003.1198387openalex-snapshot
Clustering data streams: theory and practice
inferredcites →https://doi.org/10.1109/tkde.2012.136openalex-snapshot
Incremental Learning of Concept Drift from Streaming Imbalanced Data
inferredcites →https://doi.org/10.1109/tnn.2005.845141openalex-snapshot
Survey of Clustering Algorithms
inferredcites →https://doi.org/10.1109/tpami.2010.48openalex-snapshot
A Martingale Framework for Detecting Changes in Data Streams by Testing Exchangeability
inferredcites →https://doi.org/10.1109/wgec.2008.32openalex-snapshot
A Grid and Density-Based Clustering Algorithm for Processing Data Stream
inferredcites →https://doi.org/10.1137/1.9781611972764.29openalex-snapshot
Density-Based Clustering over an Evolving Data Stream with Noise
inferredcites →https://doi.org/10.1137/1.9781611972764.72openalex-snapshot
Robust Clustering for Tracking Noisy Evolving Data Streams
inferredcites →https://doi.org/10.1145/1007352.1007400openalex-snapshot
On coresets for k-means and k-median clustering
inferredcites →https://doi.org/10.1145/1099554.1099592openalex-snapshot
Clustering high-dimensional data using an efficient and effective data space reduction
inferredcites →https://doi.org/10.1145/130226.134466openalex-snapshot
Incremental clustering for dynamic information processing
inferredcites →https://doi.org/10.1145/233269.233324openalex-snapshot
BIRCH
inferredcites →https://doi.org/10.1145/2522968.2522981openalex-snapshot
Data stream clustering
inferredcites →https://doi.org/10.1145/258533.258657openalex-snapshot
Incremental clustering and dynamic information retrieval
inferredcites →https://doi.org/10.1145/276305.276312openalex-snapshot
CURE
inferredcites →https://doi.org/10.1145/304181.304187openalex-snapshot
OPTICS
inferredcites →https://doi.org/10.1145/331499.331504openalex-snapshot
Data clustering
inferredcites →https://doi.org/10.1214/aos/1176344722openalex-snapshot
Multivariate Generalizations of the Wald-Wolfowitz and Smirnov Two-Sample Tests
inferredcites →https://doi.org/10.21236/ada439508openalex-snapshot
CLUTO - A Clustering Toolkit
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Pattern Classification and Scene Analysis.
inferredcites →https://doi.org/10.4135/9781412961288.n414openalex-snapshot
“Sequential Tests of Statistical Hypotheses”
inferredcites →https://doi.org/10.48550/arxiv.1206.6427openalex-snapshot
Convergence of the EM Algorithm for Gaussian Mixtures with Unbalanced Mixing Coefficients

What points at this work

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

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The Challenges of Big Data and the Contribution of Fuzzy Logic
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Enhancing the DISSFCM Algorithm for Data Stream Classification
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Deep Incremental Learning for Big Data Stream Analytics
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Adaptive Classifier Using Extreme Learning Machine for Classifying Twitter Data Streams
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Concept drift from 1980 to 2020: a comprehensive bibliometric analysis with future research insight
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Explaining smartphone-based acoustic data in bipolar disorder: Semi-supervised fuzzy clustering and relative linguistic summaries
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Bot recognition in a Web store: An approach based on unsupervised learning
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Detection of Hazardous Road Events From Audio Streams: An Ensemble Outlier Detection Approach
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Towards Analysing Climate Change Temperature Patterns through Stream Clustering Methods
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Intelligent analysis of data streams about phone calls for bipolar disorder monitoring
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Fuzzy Linguistic Summaries for Explaining Online Semi-Supervised Learning
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Incremental and Adaptive Fuzzy Clustering for Virtual Learning Environments Data Analysis
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Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems
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Educational Stream Data Analysis: A Case Study
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Data Stream Clustering: Introducing Recursively Extendable Aggregation Functions for Incremental Cluster Fusion Processes
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Data Stream Classification by Dynamic Incremental Semi-Supervised Fuzzy Clustering
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Soft Metaclustering for Unsupervised Recognition of Concept Drift
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WITHDRAWN: Implementation of Reliability Centered Maintenance (RCM) in the background of industry 4.0 –Issues, Challenges, and Opportunities
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Data Stream Clustering Using Fuzzy-based Evolving Cauchy Algorithm
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Balancing Data Within Incremental Semi-supervised Fuzzy Clustering for Credit Card Fraud Detection
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Merging Clusters in Summary Structures for Data Stream Mining based on Fuzzy Similarity Measures
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Credit card fraud detection by dynamic incremental semi-supervised fuzzy clustering
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The unordered time series fuzzy clustering algorithm based on the adaptive incremental learning
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Towards robust natural language and image processing In low-resource scenarios
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A Novel Density Peak Fuzzy Clustering Algorithm for Moving Vehicles Using Traffic Radar
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Explainable Artificial Intelligence for Developing Smart Cities Solutions
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Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings
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Systolizing The Adaptive Decision Feedback Equalizer Using A Symbolic State Space Formulation
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An Evolving Fuzzy Model to Determine an Optimal Number of Data Stream Clusters
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