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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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Journal ArticleDOI
Data mining for hypertext: a tutorial survey
TL;DR: Recent advances in learning and mining problems related to hypertext in general and the Web in particular are surveyed and the continuum of supervised to semi-supervised to unsupervised learning problems is reviewed.
Journal ArticleDOI
Fuzzy clustering with partial supervision
Witold Pedrycz,J. Waletzky +1 more
TL;DR: This paper presents a problem of fuzzy clustering with partial supervision, i.e., unsupervised learning completed in the presence of some labeled patterns, and proposes two specific learning scenarios of complete and incomplete class assignment of the labeled patterns.
Journal ArticleDOI
Text segmentation using Gabor filters for automatic document processing
TL;DR: In this paper, two-dimensional Gabor filters are used to extract texture features for each text region in a given document image, and the text in the document is considered as a textured region.
Journal ArticleDOI
Symbolic clustering using a new dissimilarity measure
K. Chidananda Gowda,Edwin Diday +1 more
TL;DR: A new dissimilarity measure, based on “position”, “span” and “content” of symbolic objects is proposed for symbolic clustering, and the results of the application of the algorithm on numeric data of known number of classes are described first to show the efficacy of the method.
Proceedings ArticleDOI
Exact and approximation algorithms for clustering
TL;DR: An n^ O(k1-1/d) -time algorithm for solving the k -center problem in \realsd , under L∈fty - and L2 -metrics and extends to other metrics, and to the discrete k - center problem.
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.
Journal ArticleDOI
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.