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Clustering aggregation by probability accumulation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-70659-3_46openalex-snapshot
Evidence Accumulation Clustering Based on the K-Means Algorithm
inferredcites →https://doi.org/10.1007/978-1-4419-1428-6_5195openalex-snapshot
Pattern Classification
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A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval
inferredcites →https://doi.org/10.1093/bioinformatics/btg038openalex-snapshot
Bagging to improve the accuracy of a clustering procedure
inferredcites →https://doi.org/10.1109/34.574797openalex-snapshot
Feature selection: evaluation, application, and small sample performance
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Large-scale parallel data clustering
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A robust competitive clustering algorithm with applications in computer vision
inferredcites →https://doi.org/10.1109/3477.678640openalex-snapshot
Conceptual clustering in information retrieval
inferredcites →https://doi.org/10.1109/icpr.1996.547613openalex-snapshot
Large-scale parallel data clustering
inferredcites →https://doi.org/10.1109/icpr.2002.1047450openalex-snapshot
Data clustering using evidence accumulation
inferredcites →https://doi.org/10.1109/tpami.2005.113openalex-snapshot
Combining multiple clusterings using evidence accumulation
inferredcites →https://doi.org/10.1137/1.9781611972740.35openalex-snapshot
A Mixture Model for Clustering Ensembles
inferredcites →https://doi.org/10.1145/1015330.1015414openalex-snapshot
Solving cluster ensemble problems by bipartite graph partitioning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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