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Paper Citation Record · LEDGER

A novel k-means clustering approach using two distance measures for Gaussian data

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.

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pith.paper-citation-record.v1
2511.17823 v2

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measured 28 of 28 reference resolution

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Outbound references

Observation 8331e236-f832-4792-ab7f-5e2c52656488 · outbound

This paper cites Supervised Learning.

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

This paper cites Prentice- Hall, Inc., 1988.

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

This paper cites Unsupervised Learn- ing.

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

This paper cites Deep Reinforcement Learning: An Overview.

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

This paper cites An Improved Genetick-means Algorithm for Opti- mal Clustering.

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

This paper cites Algorithmic Complexity: Three NP-hard problems in Com- putational Statistics.

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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This paper cites Using Metaheuristic Algorithms to Improvek-Means Clus- tering: A Comparative Study.

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

This paper cites A Selection Process for Genetic Algorithm Using Clus- tering Analysis.

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

This paper cites Genetick-means Clustering Algo- rithm for Mixed Numeric and Categorical Data Sets.

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

This paper cites Genetic Algorithm based onk-means Clustering Tech- nique for Multi-Objective Resource Allocation Problems.

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

This paper cites Survey of Clustering Algorithms.

A novel k-means clustering approach using two distance measures for Gaussian data Survey of Clustering Algorithms

Reference 11

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A novel k-means clustering approach using two distance measures for Gaussian data Unresolved cited work

Reference 12

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This paper cites Data Mining in Education.

A novel k-means clustering approach using two distance measures for Gaussian data Data Mining in Education

Reference 13

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This paper cites Unsupervisedk-means Clustering Algorithm.

A novel k-means clustering approach using two distance measures for Gaussian data Unsupervisedk-means Clustering Algorithm

Reference 14

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This paper cites A Survey of Kernel and Spectral Methods for Clus- tering.

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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This paper cites Domain wall-grain boundary interactions in polycrystalline Pb(Zr0.7Ti0.3)O3 piezoceramics.

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

This paper cites The Globalk-means Clustering Algorithm.

A novel k-means clustering approach using two distance measures for Gaussian data The Globalk-means Clustering Algorithm

Reference 17

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This paper cites Selection ofkink- means clustering.

A novel k-means clustering approach using two distance measures for Gaussian data Selection ofkink- means clustering

Reference 18

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This paper cites A Comparative Study of Efficient Initialization Methods for thek-means Clustering Algo- rithm.

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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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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This paper cites K-means with Three dif- ferent Distance Metrics.

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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This paper cites Inter Cluster Distance Man- agement Model with Optimal Centroid Estimation fork-means Clustering Al- gorithm.

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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This paper cites [Online; accessed 13-June-2022].

A novel k-means clustering approach using two distance measures for Gaussian data [Online; accessed 13-June-2022]

Reference 23

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This paper cites 2017.url: http://archive.ics.uci.edu/ml.

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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This paper cites Extensions ofk-means Type Algorithms: A New Clustering Framework by Integrating Intracluster Com- pactness and Intercluster Separation.

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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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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This paper cites Two Improvedk-means Algorithms.

A novel k-means clustering approach using two distance measures for Gaussian data Two Improvedk-means Algorithms

Reference 27

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A novel k-means clustering approach using two distance measures for Gaussian data Exploring Property Based Aluminum Specifications

Reference 28

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