On the public citation graph
A Grid-Based Clustering Algorithm for High-Dimensional Data Streams
0 signed · 43 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-24655-8_44openalex-snapshot
Clustering Data Streams On the Two-Tier Structure
inferredcites →https://doi.org/10.1007/s007780050009openalex-snapshot
WaveCluster: a wavelet-based clustering approach for spatial data in very large databases
inferredcites →https://doi.org/10.1016/b978-012088469-8.50075-9openalex-snapshot
A Framework for Projected Clustering of High Dimensional Data Streams
inferredcites →https://doi.org/10.1016/b978-012722442-8/50016-1openalex-snapshot
A Framework for Clustering Evolving Data Streams
inferredcites →https://doi.org/10.1109/icde.2002.994785openalex-snapshot
Streaming-data algorithms for high-quality clustering
inferredcites →https://doi.org/10.1109/icdm.2004.10112openalex-snapshot
Subspace Selection for Clustering High-Dimensional Data
inferredcites →https://doi.org/10.1109/tkde.2003.1198387openalex-snapshot
Clustering data streams: theory and practice
inferredcites →https://doi.org/10.1145/276304.276314openalex-snapshot
Automatic subspace clustering of high dimensional data for data mining applications
inferredcites →https://doi.org/10.1145/304181.304188openalex-snapshot
Fast algorithms for projected clustering
inferredcites →https://doi.org/10.1145/304182.304188openalex-snapshot
Fast algorithms for projected clustering
inferredcites →https://doi.org/10.1145/507515.507519openalex-snapshot
Requirements for clustering data streams
inferredcites →https://doi.org/10.1145/564691.564739openalex-snapshot
A Monte Carlo algorithm for fast projective clustering
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/11906070_4openalex-snapshot
A Grid-Based Subspace Clustering Algorithm for High-Dimensional Data Streams
inferred← citeshttps://doi.org/10.1007/978-3-030-30490-4_46openalex-snapshot
Soft Subspace Growing Neural Gas for Data Stream Clustering
inferred← citeshttps://doi.org/10.1007/978-3-319-11056-1_4openalex-snapshot
Stream Clustering Algorithms: A Primer
inferred← citeshttps://doi.org/10.1007/978-3-540-74469-6_61openalex-snapshot
Exclusive and Complete Clustering of Streams
inferred← citeshttps://doi.org/10.1007/978-3-642-16515-3_12openalex-snapshot
A Clustering Algorithm Based on Matrix over High Dimensional Data Stream
inferred← citeshttps://doi.org/10.1007/s00357-017-9222-1openalex-snapshot
Versatile Hyper-Elliptic Clustering Approach for Streaming Data Based on One-Pass-Thrown-Away Learning
inferred← citeshttps://doi.org/10.1007/s00521-020-05184-zopenalex-snapshot
Subspace data stream clustering with global and local weighting models
inferred← citeshttps://doi.org/10.1007/s10115-013-0659-1openalex-snapshot
Clustering data streams using grid-based synopsis
inferred← citeshttps://doi.org/10.1007/s10115-025-02484-5openalex-snapshot
Data stream clustering with concept drift using fractal dimension
inferred← citeshttps://doi.org/10.1007/s10462-020-09874-xopenalex-snapshot
Data stream clustering: a review
inferred← citeshttps://doi.org/10.1016/j.datak.2025.102484openalex-snapshot
TEDA-driven adaptive stream clustering for concept drift detection
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122055openalex-snapshot
Colossal Trajectory Mining: A unifying approach to mine behavioral mobility patterns
inferred← citeshttps://doi.org/10.1109/access.2021.3134704openalex-snapshot
A Systematic Review of Density Grid-Based Clustering for Data Streams
inferred← citeshttps://doi.org/10.1109/access.2025.3596435openalex-snapshot
On Evaluation of Data Stream Clustering Algorithms: A Survey
inferred← citeshttps://doi.org/10.1109/cdee.2010.48openalex-snapshot
Density-Based Data Streams Subspace Clustering over Weighted Sliding Windows
inferred← citeshttps://doi.org/10.1109/csie.2009.540openalex-snapshot
Research and Implementation of Network Transmission Situation Awareness
inferred← citeshttps://doi.org/10.1109/cybconf.2015.7175917openalex-snapshot
Fast grid-based clustering method for automatic calculation of optimal parameters of skin color classifier for head tracking
inferred← citeshttps://doi.org/10.1109/eais58494.2024.10570034openalex-snapshot
Towards Analysing Climate Change Temperature Patterns through Stream Clustering Methods
inferred← citeshttps://doi.org/10.1109/iciea.2008.4582959openalex-snapshot
Clustering high dimensional data streams at multiple time granularities
inferred← citeshttps://doi.org/10.1109/icis.2009.95openalex-snapshot
Identifying Structures with Informative Dimensions in Streams
inferred← citeshttps://doi.org/10.1134/s1064226915120177openalex-snapshot
Combinatorial clustering: Literature review, methods, examples
inferred← citeshttps://doi.org/10.1371/journal.pone.0339171openalex-snapshot
H-NGPCA: Hierarchical clustering of data streams with adaptive number of clusters and adaptive dimensionality
inferred← citeshttps://doi.org/10.2478/acss-2020-0011openalex-snapshot
A Systematic Comparative Analysis of Clustering Techniques
inferred← citeshttps://doi.org/10.3390/s23031520openalex-snapshot
Online-Dynamic-Clustering-Based Soft Sensor for Industrial Semi-Supervised Data Streams
inferred← citeshttps://doi.org/10.4156/ijact.vol3.issue8.18openalex-snapshot
Clustering over High-Dimensional Data Streams Based on Grid Density and Effective Dimension
inferred← citeshttps://doi.org/10.5120/21577-4636openalex-snapshot
Exploratory Implementation of Stream Clustering Algorithm using MongoDB
inferred← citeshttps://doi.org/10.5120/ijca2018918014openalex-snapshot
A Survey on Clustering Algorithms for Data Streams
inferred← citeshttps://doi.org/10.70675/9778aca1z6601z4723za496z164c85caa7f9openalex-snapshot
Subspace clustering on static datasets and dynamic data streams using bio-inspired algorithms
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.