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1
Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…Determining the suitable algorithm which can bring the optimized group clusters could be an issue. …”
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Thesis -
2
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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3
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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4
Customer segmentation on clustering algorithms
Published 2023“…This report presents an analysis of customer segmentation using various clustering algorithms, including k-means, DBSCAN, GMM, and RFM. …”
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5
Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison
Published 2006“…The results of the SOM neural networks, Wards and Group-Average methods are evaluated for the clustering of different biologically active chemical molecules that can be used as drug like compounds based on topological descriptors. …”
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6
Transitive fuzzy similarity multigraph-based model for alternative clustering in multi-criteria group decision making problems
Published 2022“…The present paper contributes to considering a novel data clustering algorithm, called FBC-Cluster, based on fuzzy multigraphs in terms of both structural and attribute similarities. …”
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7
Data clustering using the bees algorithm
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8
Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison
Published 2006“…The results of the SOM neural networks, Wards and Group-Average methods are evaluated for the clustering of different biologically active chemical molecules that can be used as drug like compounds based on topological descriptors. …”
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9
Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…Exploring the dataset features through the application of clustering algorithms is a viable means by which the conceptual description of such data can be revealed for better understanding, grouping and decision making. …”
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10
Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
Article -
11
Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
12
Evaluation of the effectiveness of clustering algorithm in retrieving Malay documents / Aminah Mahmood
Published 2004“…Second experiment use stenmiing method. Finally, the last experiment uses combination of stemming and clustering methods.…”
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13
A study of density-grid based clustering algorithms on data streams
Published 2011“…In this paper we review the grid based clustering algorithms that use density-based algorithms or density concept for the clustering. …”
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14
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
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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15
Optimized clustering with modified K-means algorithm
Published 2021“…The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
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16
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…Clustering, an unsupervised method of grouping sets of data, is used as a solution technique in various fields to divide and restructure data to become more significant and transform them into more useful information. …”
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17
Adaptive firefly algorithm for hierarchical text clustering
Published 2016“…The proposed Adaptive Firefly Algorithm (AFA) consists of three components: document clustering, cluster refining, and cluster merging. …”
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Thesis -
18
ChoCD : Usable and secure graphical password authentication scheme
Published 2024thesis::master thesis -
19
Automatic clustering of gene ontology by genetic algorithm
Published 2006“…Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. …”
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20
Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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