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Showing 1 - 20 results of 239 for search '(((( data making algorithm ) OR ( data clustering algorithm ))) OR ( elements data algorithm ))', query time: 0.15s Refine Results
  1. 1
    An enhanced k-means clustering algorithm for pattern discovery in healthcare data

    An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

    Published 2015
    “…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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  2. 2
    Improved search-tree algorithms for the cluster edit problem. (c2011)

    Improved search-tree algorithms for the cluster edit problem. (c2011) by Ghrayeb, Ali Kassem

    Published 2011
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  3. 3
    Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique

    Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

    Published 2024
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  4. 4
    HIERARCHAL CLUSTERING ALGORITHM FOR LARGE XML DATA

    HIERARCHAL CLUSTERING ALGORITHM FOR LARGE XML DATA by unknown

    Published 2020
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  5. 5
    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT

    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
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  6. 6
    A Survey of Data Clustering Techniques

    A Survey of Data Clustering Techniques by Sobeh, Salma

    Published 2023
    Subjects: “…Cluster analysis -- Data processing…”
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  7. 7
    Clustering/partitioning algorithms and comparative analysis

    Clustering/partitioning algorithms and comparative analysis by Touma, Walid Rachid

    Published 1989
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  8. 8
    A Novel Iterative non-Deterministic Algorithm for the Data Clustering Problem

    A Novel Iterative non-Deterministic Algorithm for the Data Clustering Problem by unknown

    Published 2020
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  9. 9
    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data

    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by Assaf, Ali

    Published 2022
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  10. 10
    Damage assessment & recovery from malicious transactions using data dependency for deffensive information warfare. (c2006)

    Damage assessment & recovery from malicious transactions using data dependency for deffensive information warfare. (c2006) by Zeitunlian, Arda

    Published 2006
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  11. 11
    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai

    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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  12. 12
    Correlation Clustering with Overlaps

    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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  13. 13
    Correlation Clustering via s-Club Cluster Edge Deletion

    Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

    Published 2023
    Subjects: “…Cluster analysis -- Data processing…”
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  14. 14
    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering

    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    Subjects: “…Data clustering…”
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  15. 15
    A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM

    A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM by Selim, S.Z.

    Published 2020
    “…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. …”
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  16. 16
    NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM

    NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM by Kamel, M.S.

    Published 2020
    “…Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. …”
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  17. 17
    Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence

    Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

    Published 2020
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  18. 18
    Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations

    Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations by Shameem A. Puthiya Parambath (14150997)

    Published 2022
    “…Here we propose a two-stage algorithm based on soft clustering to provide an efficient solution to this problem. …”
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  19. 19
    (k, l)-Clustering for Transactional Data Streams Anonymization

    (k, l)-Clustering for Transactional Data Streams Anonymization by Tekli, Jimmy

    Published 2018
    “…We evaluate our algorithm in terms of utility by considering two different (k, l)-clustering approaches.…”
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  20. 20
    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm

    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…Among these, K-means is widely used for efficiently solving clustering problems. This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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