Paper Citation Record · LEDGER

Interpretable Clustering Ensemble

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2506.05877.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.05877 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:18:07.823391Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ae9a20b-8235-47e3-992f-8e430c7d09de · outbound

This paper cites Data clustering: application and trends,.

Interpretable Clustering Ensemble Data clustering: application and trends,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 012959c3-23b0-4f2e-b589-d65a3e6ea2b2 · outbound

This paper cites A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets,.

Interpretable Clustering Ensemble A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:18:08.248775Z

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Observation 2103fc12-6bd4-4f65-8b55-47565280db14 · outbound

This paper cites Co-citation and cluster analyses of extant literature on social networks,.

Interpretable Clustering Ensemble Co-citation and cluster analyses of extant literature on social networks,

Reference 3

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Observation 03058886-50a2-4a1f-8381-97bfad528721 · outbound

This paper cites Cluster analysis for gene expression data: a survey,.

Interpretable Clustering Ensemble Cluster analysis for gene expression data: a survey,

Reference 4

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Observation 9e19592b-89b7-4944-bf54-1bbc000efa73 · outbound

This paper cites From clustering to clustering ensemble selection: A review,.

Interpretable Clustering Ensemble From clustering to clustering ensemble selection: A review,

Reference 5

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Observation 924c8b60-aa38-4ae8-b8ec-b9581d6f4ad9 · outbound

This paper cites Interpretable Clustering: A Survey.

Interpretable Clustering Ensemble Interpretable Clustering: A Survey

Reference 6

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Observation bfab759d-0e76-4f40-b6a0-4281803edfb5 · outbound

This paper cites Shallow decision trees for ex- plainable k-means clustering,.

Interpretable Clustering Ensemble Shallow decision trees for ex- plainable k-means clustering,

Reference 7

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Observation efda30df-ceeb-482b-a0e6-18487dff57e9 · outbound

This paper cites Interpretable clustering: an optimization approach,.

Interpretable Clustering Ensemble Interpretable clustering: an optimization approach,

Reference 8

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Observation af70b69e-4666-44ab-86ae-e2def715c967 · outbound

This paper cites A survey of clustering ensemble algorithms,.

Interpretable Clustering Ensemble A survey of clustering ensemble algorithms,

Reference 9

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Observation a6484efb-fbc5-4a19-a537-f8f591386c24 · outbound

This paper cites Cluster ensembles: A survey of ap- proaches with recent extensions and applications,.

Interpretable Clustering Ensemble Cluster ensembles: A survey of ap- proaches with recent extensions and applications,

Reference 10

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Observation 955fa1b3-c23d-4ebd-9042-3447f23a8ed6 · outbound

This paper cites Cluster ensembles — A knowledge reuse framework for combining multiple partitions,.

Interpretable Clustering Ensemble Cluster ensembles — A knowledge reuse framework for combining multiple partitions,

Reference 11

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Observation 87825cac-38ed-41b9-b690-5df2c6e30725 · outbound

This paper cites Solving cluster ensemble problems by bipartite graph partitioning,.

Interpretable Clustering Ensemble Solving cluster ensemble problems by bipartite graph partitioning,

Reference 12

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Observation 65fe2446-a90a-4a6e-8852-fbac260ef65c · outbound

This paper cites Combining multiple clusterings using evidence accumulation,.

Interpretable Clustering Ensemble Combining multiple clusterings using evidence accumulation,

Reference 13

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Source-reported events for the cited work

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Observation 028fcac7-9b3d-444b-8a43-7772378e1231 · outbound

This paper cites Ensemble clustering via ran- dom walker consensus strategy,.

Interpretable Clustering Ensemble Ensemble clustering via ran- dom walker consensus strategy,

Reference 14

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Observation 5852ac04-5e15-4628-ac51-c469dd320ea0 · outbound

This paper cites Clustering aggregation by probability accumulation,.

Interpretable Clustering Ensemble Clustering aggregation by probability accumulation,

Reference 15

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Observation 572ac241-cf0c-4d39-b1b3-06a169bd44f0 · outbound

This paper cites Active clustering ensemble with self-paced learning,.

Interpretable Clustering Ensemble Active clustering ensemble with self-paced learning,

Reference 16

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Observation be02ac84-6e7c-4063-aeeb-08b4ede1e81b · outbound

This paper cites Adaptive weighted ensemble clustering via kernel learning and local information preserva- tion,.

Interpretable Clustering Ensemble Adaptive weighted ensemble clustering via kernel learning and local information preserva- tion,

Reference 17

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Observation 0fff0784-2bf8-4081-af81-a84296ea83fd · outbound

This paper cites A multiple clustering combination approach based on iterative voting process,.

Interpretable Clustering Ensemble A multiple clustering combination approach based on iterative voting process,

Reference 18

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Observation 9d83bb94-fd4e-4e19-9871-0fbea489bc99 · outbound

This paper cites On voting-based consensus of cluster ensembles,.

Interpretable Clustering Ensemble On voting-based consensus of cluster ensembles,

Reference 19

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Observation f6cc57d8-e4d2-428f-8b9f-1d3807452655 · outbound

This paper cites V oting-based consensus clustering for combining multiple clusterings of chemical structures,.

Interpretable Clustering Ensemble V oting-based consensus clustering for combining multiple clusterings of chemical structures,

Reference 20

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Observation c373c648-2ee0-4191-93ef-a96acb3714ba · outbound

This paper cites On clustering and interpreting with rules by means of mathematical op- timization,.

Interpretable Clustering Ensemble On clustering and interpreting with rules by means of mathematical op- timization,

Reference 21

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Observation 48967cc7-c0c2-4fa3-9ada-507ccff3738d · outbound

This paper cites Interpretable clustering using unsupervised binary trees,.

Interpretable Clustering Ensemble Interpretable clustering using unsupervised binary trees,

Reference 22

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Observation b069a2c7-12ae-498c-b9e9-ae967b3b4174 · outbound

This paper cites Xclusters: explainability-first clustering,.

Interpretable Clustering Ensemble Xclusters: explainability-first clustering,

Reference 23

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Observation ce427d00-ae36-4345-9612-45d7e0c4a775 · outbound

This paper cites Interpret- ing clusters via prototype optimization,.

Interpretable Clustering Ensemble Interpret- ing clusters via prototype optimization,

Reference 24

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Observation c0041f6d-f1f6-4391-bfa2-e06949016e8f · outbound

This paper cites Cluster explanation via polyhedral descrip- tions,.

Interpretable Clustering Ensemble Cluster explanation via polyhedral descrip- tions,

Reference 25

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Observation 81583f9a-588e-42bf-993f-b39cf21d5256 · outbound

This paper cites The cluster description problem- complexity results, formulations and approximations,.

Interpretable Clustering Ensemble The cluster description problem- complexity results, formulations and approximations,

Reference 26

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Observation 12497f1f-dbf0-490e-b530-08e980deb933 · outbound

This paper cites Time2feat: Learn- ing interpretable representations for multivariate time series clustering,.

Interpretable Clustering Ensemble Time2feat: Learn- ing interpretable representations for multivariate time series clustering,

Reference 27

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Observation c1b2f5f5-1973-46a9-9467-6529834d4714 · outbound

This paper cites Interpretable Deep Clustering for Tabular Data.

Interpretable Clustering Ensemble Interpretable Deep Clustering for Tabular Data

Reference 28

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Observation 0fe38b46-ed67-48bc-bf67-95c7fd72d7e3 · outbound

This paper cites Interpretable clustering of students’ solutions in introductory programming,.

Interpretable Clustering Ensemble Interpretable clustering of students’ solutions in introductory programming,

Reference 29

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Observation b2a38d51-d394-4db4-a09f-6f320a239a58 · outbound

This paper cites Balancing the tradeoff between clustering value and interpretability,.

Interpretable Clustering Ensemble Balancing the tradeoff between clustering value and interpretability,

Reference 30

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Observation 306b2834-29b7-489d-b5e4-538cd29c80f5 · outbound

This paper cites Explainable k-means and k-medians clustering,.

Interpretable Clustering Ensemble Explainable k-means and k-medians clustering,

Reference 31

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Observation cea3344e-bd3c-4c74-ab52-bec58df0b877 · outbound

This paper cites To cluster, or not to cluster: An analysis of clusterability methods,.

Interpretable Clustering Ensemble To cluster, or not to cluster: An analysis of clusterability methods,

Reference 32

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Observation a33efe16-cda7-4e5a-8dc7-1aac1c203931 · outbound

This paper cites Bootstrapping for signifi- cance of compact clusters in multidimensional datasets,.

Interpretable Clustering Ensemble Bootstrapping for signifi- cance of compact clusters in multidimensional datasets,

Reference 33

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Observation f94dbd01-7d35-47c3-af2c-d248ecea98dd · outbound

This paper cites Nonparametric cluster significance testing with reference to a unimodal null distribution,.

Interpretable Clustering Ensemble Nonparametric cluster significance testing with reference to a unimodal null distribution,

Reference 34

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Observation a14a897a-9a67-4ee1-8b69-c975ce397276 · outbound

This paper cites Significant dbscan+: Statistically robust density-based clustering,.

Interpretable Clustering Ensemble Significant dbscan+: Statistically robust density-based clustering,

Reference 35

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Observation c42f3348-2d19-47b1-a5a3-ebdd3d8ef345 · outbound

This paper cites Interpretable categorical data clustering via hypothesis testing,.

Interpretable Clustering Ensemble Interpretable categorical data clustering via hypothesis testing,

Reference 36

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Observation 69effc39-431d-463a-923d-b14682cc13e1 · outbound

This paper cites Significance-based decision tree for interpretable categorical data clustering,.

Interpretable Clustering Ensemble Significance-based decision tree for interpretable categorical data clustering,

Reference 37

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Observation 7b3468a9-2c56-4d31-9352-7e7e68f3d91a · outbound

This paper cites Significance-based interpretable sequence clustering,.

Interpretable Clustering Ensemble Significance-based interpretable sequence clustering,

Reference 38

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Source-reported events for the cited work

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Observation 2409a520-7950-4da9-a4c6-9af4008c38c7 · outbound

This paper cites Agresti,Categorical data analysis.

Interpretable Clustering Ensemble Agresti,Categorical data analysis

Reference 39

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Observation 3e047c4c-b1f7-49d0-a828-496ca28c3cea · outbound

This paper cites Locally weighted ensemble clustering,.

Interpretable Clustering Ensemble Locally weighted ensemble clustering,

Reference 40

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Source-reported events for the cited work

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Observation 9d8cbf5d-3110-4fe6-b7a6-f501d50d52a4 · outbound

This paper cites Ensemble clustering via co- association matrix self-enhancement,.

Interpretable Clustering Ensemble Ensemble clustering via co- association matrix self-enhancement,

Reference 41

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Observation 24ecca7e-71ee-4030-b909-b458545d2f96 · outbound

This paper cites Enhanced ensemble clustering via fast propagation of cluster-wise similarities,.

Interpretable Clustering Ensemble Enhanced ensemble clustering via fast propagation of cluster-wise similarities,

Reference 42

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Observation a1c9dad5-4c9a-484c-af77-c769dbf1a46f · outbound

This paper cites Uci machine learning repository,.

Interpretable Clustering Ensemble Uci machine learning repository,

Reference 43

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Observation 6aa111da-87ad-4aa2-a1e9-e350b6107911 · outbound

This paper cites Keel data-mining software tool: Data set repository, integration of algorithms and experi- mental analysis framework,.

Interpretable Clustering Ensemble Keel data-mining software tool: Data set repository, integration of algorithms and experi- mental analysis framework,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:18:07.879097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.