On the Approximation of Correlation Clustering and Consensus Clustering
نویسندگان
چکیده
منابع مشابه
On the Approximation of Correlation Clustering and Consensus Clustering
The Correlation Clustering problem has been introduced recently [N. Bansal, A. Blum, S. Chawla, Correlation Clustering, in: Proc. 43rd Symp. Foundations of Computer Science, FOCS, 2002, pp. 238–247] as a model for clustering data when a binary relationship between data points is known. More precisely, for each pair of points we have two scores measuring the similarity and dissimilarity respecti...
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با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
Entropy-based Consensus for Distributed Data Clustering
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Consensus clustering and meta clustering are two important extensions of the classical clustering problem. Given a set of input clusterings of a given dataset, consensus clustering aims to find a single final clustering which is a better fit in some sense than the existing clusterings, and meta clustering aims to group similar input clusterings together so that users only need to examine a smal...
متن کاملAre approximation algorithms for consensus clustering worthwhile?
Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated a number of approximation algorithms for consensus clustering and similar problems. These algorithms run in polynomial time, with performance guaranteed to be at most a certain factor worse than optimal. We investigat...
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ژورنال
عنوان ژورنال: Journal of Computer and System Sciences
سال: 2008
ISSN: 0022-0000
DOI: 10.1016/j.jcss.2007.06.024