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GRAPH CLUSTERING USING RESTRICTED NEIGHBOURHOOD SEARCH ALGORITHM: AN ADVANCED STUDY OF IMPLEMENTATION AND BEHAVIOURAL ANALYSIS - Softcover
Inhaltsangabe
Restricted Neighborhood Search Algorithm(R.N.S.C)is a cost-based clustering technique for clustering the graph into separate clusters, where each cluster has some similar properties.Based on a practitioner's insights, the book focuses on the basic principles and dwells on the complex details of graph clustering using Restricted Neighbourhood Search. The book covers the following: Introduction Experimental results Test Data Random graph Color benchmark graph Parameter training and statistical results Cluster limit Diversification Tabu length Search length Graph coloring
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Über die Autorin bzw. den Autor
He is currently Assistant Professor,Department of Computer Science at Invertis University, Bareilly.He has done his post-graduation from Amity University and Research Thesis from Indian Institute of Technology, Banaras Hindu University, Varanasi.He has three papers in International Journal(I.J.C.A.)and one in National Journal(Samriddhi).
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GRAPH CLUSTERING USING RESTRICTED NEIGHBOURHOOD SEARCH ALGORITHM
Verlag:
LAP Lambert Academic Publishing Sep 2012, 2012
ISBN 10: 3659237132
ISBN 13: 9783659237133
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Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -Restricted Neighborhood Search Algorithm(R.N.S.C)is a cost-based clustering technique for clustering the graph into separate clusters, where each cluster has some similar properties.Based on a practitioner's insights, the book focuses on the basic principles and dwells on the complex details of graph clustering using Restricted Neighbourhood Search. The book covers the following: Introduction Experimental results Test Data Random graph Color benchmark graph Parameter training and statistical results Cluster limit Diversification Tabu length Search length Graph coloringBooks on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch. Artikel-Nr. 9783659237133
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