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Novel multi-centroid, multi-run sampling schemes for K-mediods-based algorithms

John F. Roddick, +2 more
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TLDR
Experimental results demonstrate the proposed scheme can not only reduce by more than 80% computation time but also reduce the average distance per object compared with CLARA and CLARANS, and IMCMRS is also superior to MCMRS.
About: 
The article was published on 2004-01-01 and is currently open access. It has received 1 citations till now. The article focuses on the topics: Sampling (statistics) & Centroid.

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Journal Article

Compact Indexes Based on Core Content in Personal Dataspace Management System

Ning Wang, +3 more
- 24 Jun 2014 - 
TL;DR: This paper refers to the most important and representative semantics from documents as core content, and build compact index, and proposes algorithm for selecting core content from a document based on semantic analysis, which can process English and Chinese documents uniformly.
References
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Book

Genetic algorithms in search, optimization, and machine learning

David E. Goldberg
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI

Optimization by Simulated Annealing

Scott Kirkpatrick, +2 more
- 13 May 1983 - 
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Proceedings Article

A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise

Martin Ester, +3 more
TL;DR: In this paper, a density-based notion of clusters is proposed to discover clusters of arbitrary shape, which can be used for class identification in large spatial databases and is shown to be more efficient than the well-known algorithm CLAR-ANS.
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An Algorithm for Vector Quantizer Design

Y. Linde, +2 more
- 01 Jan 1980 - 
TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.
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Finding Groups in Data: An Introduction to Chster Analysis

Ali S. Hadi
- 01 Sep 1991 - 
TL;DR: This book make understandable the cluster analysis is based notion of starsmodern treatment, which efficiently finds accurate clusters in data and discusses various types of study the user set explicitly but also proposes another.