Results 11 to 20 of about 4,729 (197)
International Journal of Distributed Sensor Networks, 2021 The tremendous growth of Internet of Medical Things has led to a surge in medical user data, and medical data publishing can provide users with numerous services. However, neglectfully publishing the data may lead to severe leakage of user’s privacy.
Zekun Zhang +3 more
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Barekeng, 2023 Cluster analysis is a technique for grouping objects in a database based on their similar characteristics. The grouping results are said to be good if each cluster is homogeneous, and can be validated using the silhouette coefficient test.
Taufiq Akbar +2 more
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Sistemasi: Jurnal Sistem Informasi, 2022 Nowadays, e-commerce data transactions are commonly used by companies to provide new information. The data transaction can reveal customer segmentation or groups based on the similar characteristics and behavior of each customer.
Romadansyah Siagian +2 more
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A hybrid heuristic for the k-medoids clustering problem [PDF]
Proceedings of the 14th annual conference on Genetic and evolutionary computation, 2012 Clustering is an important tool for data analysis, since it allows the exploration of datasets with no or very little prior information. Its main goal is to group a set of data based on their similarity (dissimilarity). A well known mathematical formulation for clustering is the k-medoids problem.
Mariá Cristina Vasconcelos Nascimento +2 more
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CoRR, 2016 We run experiments showing that algorithm clarans (Ng et al., 2005) finds better K-medoids solutions than the Voronoi iteration algorithm. This finding, along with the similarity between the Voronoi iteration algorithm and Lloyd's K-means algorithm, suggests that clarans may be an effective K-means initializer.
James Newling, François Fleuret
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K-Medoids Clustering of Data Sequences With Composite Distributions [PDF]
IEEE Transactions on Signal Processing, 2019 This paper studies clustering of data sequences using the k-medoids algorithm. All the data sequences are assumed to be generated from \emph{unknown} continuous distributions, which form clusters with each cluster containing a composite set of closely located distributions (based on a certain distance metric between distributions).
Tiexing Wang +5 more
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Analisis Permasalahan Perangkat Pencetak Menggunakan Metode Algoritma K-Means dan K-Medoids
Teknika, 2022 Amido Makmor Tulus Sejati merupakan perusahaan distributor multifunction printer merek Kyocera di Indonesia. Evaluasi kinerja teknisi diperlukan untuk mempertahankan kepuasan customer terhadap penggunaan multifunction printer Kyocera.
Fadli Aziz Setiawan +2 more
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Hybrid Personalized Recommender System Using Fast K-medoids Clustering Algorithm
Journal of Advances in Information Technology, 2011 Recommender systems attempt to predict items in which a user might be interested, given some information about the user’s and items’ profiles.
Subhash K. Shinde, Uday V. Kulkarni
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Comparison analysis of Euclidean and Gower distance measures on k-medoids cluster
Jurnal Teknologi dan Sistem Komputer, 2021 K-medoids clustering uses distance measurement to find and classify data that have similarities and inequalities. The distance measurement method selection can affect the clustering performance for a dataset.
Agil Aditya +2 more
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Journal of Marine Science and Engineering, 2021 The modern discrimination of sediment is based on acoustic intensity (backscatter) information from high-resolution multibeam echo-sounder systems (MBES).
Xiaochen Yu +4 more
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