Results 31 to 40 of about 866,547 (282)
Entropy, 2022 Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a widely used algorithm for exploratory clustering applications. Despite the DBSCAN algorithm being considered an unsupervised pattern recognition method, it has two parameters that ...
Juan Carlos Perafan-Lopez +3 more
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Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering [PDF]
, 2008 As the common clustering algorithms use vector space model (VSM) to represent document, the conceptual relationships between related terms which do not co-occur literally are ignored.
Li, Chenghua +3 more
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Fermion cluster algorithms [PDF]
Nuclear Physics B - Proceedings Supplements, 2000 LATTICE99 (algorithms & Machines), 3 pages, 4 eps figures, espcrc2 ...
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Differential evolution-based transfer rough clustering algorithm
Complex & Intelligent Systems, 2023 Due to well processing the uncertainty in data, rough clustering methods have been successfully applied in many fields. However, when the capacity of the available data is limited or the data are disturbed by noise, the rough clustering algorithms always
Feng Zhao, Chaofei Wang, Hanqiang Liu
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Ensemble Clustering Algorithm Based on Weighted Super Cluster
Jisuanji kexue yu tansuo, 2021 Most ensemble clustering algorithms use K-means to generate base clustering, but the result of base clustering is not good. And most ensemble clustering algorithms ignore the diversity of base clustering, treat base clustering equally, and generate the ...
XUE Hongyan, QIAN Xuezhong, ZHOU Shibing
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Analysis of influencing factors on excellent teachers' professional growth based on DB-Kmeans method
EURASIP Journal on Advances in Signal Processing, 2022 The Kmeans clustering algorithm is widely used for the advantages of simplicity and efficient operation. However, the lack of clustering centers in the algorithm usually causes incorrect category of some discrete points.
Xu Gao +3 more
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Journal of Intelligent Systems, 2018 The progress of databases in fields such as medical, business, education, marketing, etc., is colossal because of the developments in information technology. Knowledge discovery from such concealed bulk databases is a tedious task.
Chander Satish +2 more
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An improved fuzzy clustering image segmentation algorithm combining spatial information
Xi'an Gongcheng Daxue xuebao, 2021 In order to improve the ability of fuzzy C-means (FCM) clustering algorithm to suppress noise, an improved fuzzy clustering image segmentation algorithm was proposed.
Xudong LIU +4 more
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Cluster synchronization algorithms
Proceedings of the 2010 American Control Conference, 2010 This paper presents two approaches to achieving cluster synchronization in dynamical multi-agent systems. In contrast to the widely studied synchronization behavior, where all the coupled agents converge to the same value asymptotically, in the cluster synchronization problem studied in this paper, we require that all the interconnected agents to ...
Xia, Weiguo, Cao, Ming
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Robust structure low-rank representation in latent space [PDF]
, 2019 Subspace clustering algorithms are usually used when processing high-dimensional data, such as in computer vision. This paper presents a robust low-rank representation (LRR) method that incorporates structure constraints and dimensionality reduction for ...
Palade, Vasile +2 more
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