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Algorithms for clustering data
Anil K. Jain,Richard C. Dubes +1 more
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The article was published on 1988-01-01 and is currently open access. It has received 8586 citations till now. The article focuses on the topics: Cluster analysis & Correlation clustering.read more
Citations
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Proceedings ArticleDOI
Natural communities in large linked networks
TL;DR: This work has developed an efficient, scalable agglomerative strategy and applied it to the citation graph of the NEC CiteSeer database and finds that some communities are essentially random and thus unstable while others are natural and will appear in most clusterings.
Journal ArticleDOI
A personalized English learning recommender system for ESL students
TL;DR: An online personalized English learning recommender system capable of providing ESL students with reading lessons that suit their different interests and therefore increase the motivation to learn is developed.
Journal ArticleDOI
Parametric and non-parametric unsupervised cluster analysis
TL;DR: It is shown that, whilst both methods are capable of determining cluster validity for data sets in which clusters tend towards a multivariate Gaussian distribution, the parametric method inevitably fails for clusters which have a non-Gaussian structure whilst the scale-space method is more robust.
Journal ArticleDOI
Trustworthiness and metrics in visualizing similarity of gene expression.
TL;DR: The conjecture from the methodological results is that the self-organizing map can be recommended to complement the usual hierarchical clustering for visualizing and exploring gene expression data.
Journal ArticleDOI
Automatic Face Segmentation and Facial Landmark Detection in Range Images
TL;DR: The goal was to develop an automatic process to be embedded in a face recognition system using only depth information as input, and the segmentation approach combines edge detection, region clustering, and shape analysis to extract the face region.
References
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Journal ArticleDOI
Shortest connection networks and some generalizations
TL;DR: In this paper, the basic problem of interconnecting a given set of terminals with a shortest possible network of direct links is considered, and a set of simple and practical procedures are given for solving this problem both graphically and computationally.
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An examination of procedures for determining the number of clusters in a data set
TL;DR: A Monte Carlo evaluation of 30 procedures for determining the number of clusters was conducted on artificial data sets which contained either 2, 3, 4, or 5 distinct nonoverlapping clusters to provide a variety of clustering solutions.
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SLINK: An optimally efficient algorithm for the single-link cluster method
TL;DR: Sibson gives an O(n 2) algorithm for single-linkage clustering, and proves that this algorithm achieves the theoretically optimal lower time bound for obtaining a single- linkage dendrogram.