Search Results - (( data representation clustering algorithm ) OR ( java application based algorithm ))

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  1. 1

    USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING by MUFLIKHAH, LAILIL

    Published 2010
    “…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
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    Thesis
  2. 2

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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    Thesis
  3. 3

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
    Article
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    High performance in minimizing of term-document matrix representation for document clustering by B., Baharudin, L., Muflikhah

    Published 2009
    “…Document clustering usually involves high dimensional term space, which makes it difficult for organizing data into a small number of meaningful clusters. …”
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    Conference or Workshop Item
  6. 6

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…DARA transforms the data relational representation into a vector space representation and a clustering process is applied to group the data based on their characteristics similarity. …”
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    Thesis
  7. 7

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…As a conclusion, balancing the search behavior notably enhanced the overall performance of the three proposed frameworks and made each of them an excellent tool for data clustering.…”
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    Thesis
  8. 8

    Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing by Leong, S.H., Ong, S.H.

    Published 2017
    “…The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.…”
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    Article
  9. 9

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Data entities may belongs to further than one cluster in the fuzzy clustering (soft clustering), and a set of membership levels are allied with each group. …”
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    Article
  10. 10

    k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data by Alfred, Rayner, Shin, Kung Ke, Sainin, Mohd Shamrie, On, Chin Kim, Pandiyan, Paulraj Murugesa, Ag Ibrahim, Ag Asri

    Published 2016
    “…Due to the growing amount of data generated and stored in relational databases, relational learning has attracted the interest of researchers in recent years.Many approaches have been developed in order to learn relational data.One of the approaches used to learn relational data is Dynamic Aggregation of Relational Attributes (DARA).The DARA algorithm is designed to summarize relational data with one-to-many relations. …”
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    Book Section
  11. 11

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
  12. 12

    Unsupervised learning of image data using generative adversarial network by Rayner Alfred, Lun,, Chew Ye

    Published 2020
    “…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
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    Proceedings
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    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…Effective analysis of graph data provides a deeper understanding of the data in data mining tasks, including classification, clustering, prediction, and recommendation systems. …”
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    Article
  16. 16

    The importance of data classification using machine learning methods in microarray data by Jaber, Aws Naser, Moorthy, Kohbalan, Machap, Logenthiran, Safaai, Deris

    Published 2021
    “…One of these challenges involves high dimensional data that are redundant, irrelevant, and noisy. To alleviate this problem, this representation should be simplified. …”
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    Article
  17. 17

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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    Final Year Project / Dissertation / Thesis
  18. 18

    A Multi-Criteria Decision-Making Approach for Targeted Distribution of Smart Indonesia Card (KIP) Scholarships by Komang, Aryasa

    Published 2025
    “…Meanwhile, in the classification stage, the C5.0 algorithm achieved the highest accuracy of 97.27% from a total of 551 data points, with 80% used as training data and 20% as testing data. …”
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    Thesis
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    Social networks content analysis for peacebuilding application by Shaikh, Muniba, Salleh, Norsaremah, Abdullah, Lili Marziana

    Published 2015
    “…The proposed framework shows that twitter is most popular SN for Pb CA purpose and proposed framework presents the searching criteria and custom filters to extract the topic specific data. Moreover, the research proposes to use lexical analysis (LA) method to extract the SNs features, 1st order context representation (CR) technique to represent the context of the extracted features, DBSCAN clustering algorithm for data management by making different clusters, ranking algorithm, Log likelihood ratio and SVM techniques for content analysis and classification. …”
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    Proceeding Paper