Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T20:56:46.026107Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2511.17823.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T20:56:46.026107Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
28 of 28 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8331e236-f832-4792-ab7f-5e2c52656488 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Supervised Learning
Reference 1
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Observation 912c270e-2b74-423a-8215-0b628d8acd54 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Prentice- Hall, Inc., 1988
Reference 2
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Observation 7dfb1e04-7ed1-420f-8040-385da8fb8f22 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Unsupervised Learn- ing
Reference 3
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Observation 979e2a56-b1e3-4b5a-bb99-9b1ce39975df · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Deep Reinforcement Learning: An Overview
Reference 4
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Observation 9d7a2d88-9a58-4cdf-95fa-cea2c2b630cf · outbound
A novel k-means clustering approach using two distance measures for Gaussian data An Improved Genetick-means Algorithm for Opti- mal Clustering
Reference 5
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Observation 0f34fdf6-721e-479f-b6fb-d15d7432ef36 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Algorithmic Complexity: Three NP-hard problems in Com- putational Statistics
Reference 6
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Observation 39cbdbd6-3592-4159-a1f0-211859347693 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Using Metaheuristic Algorithms to Improvek-Means Clus- tering: A Comparative Study
Reference 7
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Observation bf7ce42a-8306-40ed-bda6-500617b5ff1d · outbound
A novel k-means clustering approach using two distance measures for Gaussian data A Selection Process for Genetic Algorithm Using Clus- tering Analysis
Reference 8
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Observation 5d5ba8ac-0583-4e38-83dd-076c4e8c2b90 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Genetick-means Clustering Algo- rithm for Mixed Numeric and Categorical Data Sets
Reference 9
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Observation 889b94bc-279b-4bd0-aa23-3b783a6c1dfc · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Genetic Algorithm based onk-means Clustering Tech- nique for Multi-Objective Resource Allocation Problems
Reference 10
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Observation e1c9eb05-d774-42b9-9a54-1f1e4299d27c · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Survey of Clustering Algorithms
Reference 11
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Observation 81290ec9-4307-422d-8e8d-88026a5fb0c1 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Unresolved cited work
Reference 12
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Observation d9542306-9112-4f82-9b72-ba9cb08056d5 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Data Mining in Education
Reference 13
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Observation b1b663a8-4be6-405e-875c-0f40785d1793 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Unsupervisedk-means Clustering Algorithm
Reference 14
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Observation c1df656c-80d1-45cf-b74b-ebf14b7d9b31 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data A Survey of Kernel and Spectral Methods for Clus- tering
Reference 15
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Observation 57691df1-9023-46a6-809e-fe473a025b21 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Domain wall-grain boundary interactions in polycrystalline Pb(Zr0.7Ti0.3)O3 piezoceramics
Reference 16
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Observation 1b21a447-4012-4247-923b-7e9f297fc45a · outbound
A novel k-means clustering approach using two distance measures for Gaussian data The Globalk-means Clustering Algorithm
Reference 17
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Observation 9d66342b-dd95-485f-8bda-15c42f35b54e · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Selection ofkink- means clustering
Reference 18
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Observation 640151b3-bc5b-49dc-af12-7519f7585e78 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data A Comparative Study of Efficient Initialization Methods for thek-means Clustering Algo- rithm
Reference 19
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Observation 9dc978b7-9eb5-4c6f-aba5-0557e8d833df · outbound
A novel k-means clustering approach using two distance measures for Gaussian data An Empirical Comparison of Four Initialization Methods for Thek-means Algorithm
Reference 20
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Observation f3d0c037-c595-40bc-9e0a-5862d37b3515 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data K-means with Three dif- ferent Distance Metrics
Reference 21
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Observation 8f310671-3508-423a-911d-962c8dfa2dc5 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Inter Cluster Distance Man- agement Model with Optimal Centroid Estimation fork-means Clustering Al- gorithm
Reference 22
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Observation f68ea18e-7be0-43d1-8fce-ea7360d348a7 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data [Online; accessed 13-June-2022]
Reference 23
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Observation b22bf917-ccff-4856-9f0d-c6dea7e47f92 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data 2017.url: http://archive.ics.uci.edu/ml
Reference 24
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Observation f8c13c41-c6ba-4330-b022-649421083dfd · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Extensions ofk-means Type Algorithms: A New Clustering Framework by Integrating Intracluster Com- pactness and Intercluster Separation
Reference 25
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Observation fd6abad8-08e2-41f1-8092-5e9d7a0a8d7c · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Cluster Center Initialization Algorithm fork-means Clustering
Reference 26
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Observation 2b153759-54ef-4fb2-99a9-ea2bde862686 · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Two Improvedk-means Algorithms
Reference 27
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Observation 1c122a36-41ba-4195-93a3-8f170cbd0adb · outbound
A novel k-means clustering approach using two distance measures for Gaussian data Exploring Property Based Aluminum Specifications
Reference 28
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No inbound Pith citation observations are available.