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  1. 1
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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  2. 2
    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data

    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

    Published 2023
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  3. 3
    Clustering mixed-type data via Dirichlet process mixture model with cluster-specific covariance matrices

    Clustering mixed-type data via Dirichlet process mixture model with cluster-specific covariance matrices by Burhanuddin, Nurul Afiqah, Ibrahim, Kamarulzaman, Zulkafli, Hani Syahida, Mustapha, Norwati

    Published 2024
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  4. 4
    Optimizing the Management of Knowledge Assets using Swarm Intelligence

    Optimizing the Management of Knowledge Assets using Swarm Intelligence by Yusof, Yuhanis, Baharom, Fauziah, Mohamed, Athraa Jasim

    Published 2018
    “…Hence, the produced clusters will be of different quality. This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. …”
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  5. 5
    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
    “…The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. …”
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  6. 6
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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  7. 7
    Drone Based Image Processing For Precision Agriculture

    Drone Based Image Processing For Precision Agriculture by Sharif, Muhammad Arif Syafiq Md

    Published 2019
    “…At first, the parallel K-means clustering algorithm was applied on the acquired image to segregate various components acquired using UAV. …”
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  8. 8
    Incremental interval type-2 fuzzy clustering of data streams using single pass method

    Incremental interval type-2 fuzzy clustering of data streams using single pass method by Qaiyum, S., Aziz, I., Hasan, M.H., Khan, A.I., Almalawi, A.

    Published 2020
    “…Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). …”
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  9. 9
    Development of a parallel clustering of bilingual corpora based on reduced terms

    Development of a parallel clustering of bilingual corpora based on reduced terms by Leow, Ching Leong

    Published 2015
    “…Document clustering is a process that groups a set of documents based on their similarities. …”
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  10. 10
    Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli

    Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli by Rosli, Muhammad Helmi

    Published 2015
    “…This can be solved by parallelizing the process in cluster environment. Most cluster environment have a variety of computer hardware specification namely heterogeneous environment.Optimizing the resources in heterogeneous environment during parallel processing is not a simple task. …”
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  11. 11
    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa

    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa by Ahmad Mustaffa, Nor Azrin

    Published 2010
    “…FCM is widely used technique in this regard but it requires the priori specification of the number of clusters. Therefore, this project is posed as one of optimization of a fuzzy cluster validity index. …”
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  12. 12
    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…It overcomes the limitations of conventional clustering algorithms in dealing with time-series data. …”
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  13. 13
    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…Additionally, the performance across four clusters demonstrates the positive impact of K-Means clustering in improving classification accuracy for specific data groups. …”
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  14. 14
    A framework for automated quality assessment of software requirement specification based on part-of-speech tagging, multi-agent k-means clustering and case-based reasoning

    A framework for automated quality assessment of software requirement specification based on part-of-speech tagging, multi-agent k-means clustering and case-based reasoning by Jubair, Mohammed Ahmed

    Published 2022
    “…However, automating the quality assessment process poses major challenges, which requires advanced Natural Language Processing (NLP) algorithms to extract the quality features, interpreting the context of the features, formulating the assessment metrics, and documenting the shortcomings as well as possible improvements. …”
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  15. 15
    Design Of Robot Motion Planning Algorithm For Wall Following Robot

    Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

    Published 2006
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  16. 16
    Individual-tree segmentation and extraction based on LiDAR point cloud data

    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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  17. 17
    An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery

    An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery by Aziz A., Essam Y., Ahmed A.N., Huang Y.F., El-Shafie A.

    Published 2023
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  18. 18
    A new clustering approach for group detection in scene-independent dense crowds

    A new clustering approach for group detection in scene-independent dense crowds by Wong, Pei Voon, Mustapha, Norwati, Affendey, Lilly Suriani, Khalid, Fatimah

    Published 2016
    “…Despite significant progress in crowd behaviour analysis over the past few years, most of today's state of the art algorithms focus on analysing individual behaviour in a specific-scene. …”
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  19. 19
    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective

    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…Each node near the cluster head join the local cluster [Wendi et al 2000]. …”
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  20. 20
    Novel techniques for enhancement and segmentation of acne vulgaris lesions

    Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

    Published 2013
    “…In addition, sensitivity and specificity are calculated for the segmentation results. …”
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