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A Survey of Data Clustering Techniques
Published 2023Subjects: “…Cluster analysis -- Data processing…”
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Clustering/partitioning algorithms and comparative analysis
Published 1989Subjects: Get full text
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masterThesis -
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A Novel Iterative non-Deterministic Algorithm for the Data Clustering Problem
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data
Published 2015“…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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Correlation Clustering via s-Club Cluster Edge Deletion
Published 2023Subjects: “…Cluster analysis -- Data processing…”
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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering
Published 2024“…<p dir="ltr">Clustering has proved to be a successful classification method when it comes to dealing with multiview data. …”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022Subjects: “…Data clustering…”
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A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM
Published 2020“…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. …”
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NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
Published 2020“…Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…Based on the similarity value, patterns are assigned to either relevant or irrelevant groups. The weak learner results are aggregated to form strong clusters, and, with the aid of voting, a majority vote is considered for designing strong clusters with minimum time. …”
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Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
Published 2022“…Here we propose a two-stage algorithm based on soft clustering to provide an efficient solution to this problem. …”
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(k, l)-Clustering for Transactional Data Streams Anonymization
Published 2018“…We evaluate our algorithm in terms of utility by considering two different (k, l)-clustering approaches.…”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Among these, K-means is widely used for efficiently solving clustering problems. This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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