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  1. 1

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  2. 2

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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    Thesis
  3. 3

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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    Thesis
  4. 4

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…In dealing with correlated variables, PCA was embedded in the proposed algorithm. The developed algorithms were tested on uncorrelated and correlated simulated data sets, generated under various conditions. …”
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    Thesis
  5. 5

    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

    Published 2016
    “…This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. …”
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    Thesis
  6. 6

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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    Thesis
  7. 7

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The paper presents test results to demonstrate the efficacy of the proposed algorithm. …”
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    Conference or Workshop Item
  8. 8

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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    Final Year Project / Dissertation / Thesis
  9. 9

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…The parallel algorithm was developed using C language with the utilization of the Message Passing Interface (MPI) library. …”
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    Citation Index Journal
  10. 10

    Computational Discovery of Motifs Using Hierarchical Clustering Techniques by Wang, Dianhui, Lee, Nung Kion

    Published 2008
    “…A mismatch based hierarchical clustering algorithm is proposed in this paper, where three heuristic rules for classifying clusters and a post-processing for ranking and refining the clusters are employed in the algorithm. …”
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    Proceeding
  11. 11

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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    Thesis
  12. 12

    Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

    Published 2014
    “…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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    Thesis
  13. 13

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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    Thesis
  14. 14

    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor by Abu Mangshor, Nur Nabilah

    Published 2010
    “…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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    Thesis
  15. 15
  16. 16

    Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

    Published 2017
    “…The technique was combining the Density Based Clustering method (DBSCAN) and firefly algorithm. Empirical tests were conducted on six standard RFID benchmark sets with random and clustered topologies. …”
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    Article
  17. 17

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…The proposed method was evaluated against five clustering approaches that have succeeded in optimization that comprises of K-means Clustering, MCPSO, IMCPSO, Spectral clustering, Birch, and average-link algorithms. …”
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    Article
  18. 18

    Evaluation of the effectiveness of clustering algorithm in retrieving Malay documents / Aminah Mahmood by Mahmood, Aminah

    Published 2004
    “…This study has evaluated and identified the effectiveness of clustering algorithm in Malay document retrieval system using Hadith test collections, which consists of Hadith documents, relevant judgments and one set of queries. …”
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    Thesis
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  20. 20

    Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

    Published 2025
    “…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
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    Thesis