San Francisco / San Mateo / Athens / Santiago / Melbourne / London / Freeman / /
Company
Geographic Information Systems / ACM Press / AAAI Press / Prentice-Hall Inc. / Geographical Information Systems / John Wiley & Sons / /
Country
Netherlands / Chile / United States / Australia / United Kingdom / Greece / / /
Facility
University of Bonn / The University of Newcastle / /
IndustryTerm
randomly-chosen solution / nd approximate solutions / hierarchical clustering algorithms / spatial data mining / local search heuristics / cient tabu search procedure / cient algorithms / search graph / local search hill-climbers / approximation algorithms / nement clustering algorithms / search halts / polynomial algorithms / unit network / genetic algorithm / bidimensional dynamic programming algorithms / genetic algorithms / random solution / tabu search / dynamic programming algorithms / large geo-referenced data sets local search hill-climbers / p-media problem / empty groups / search space / /
OperatingSystem
Xp / /
Organization
American Statistical Association / A.T. Murray and R.L. Church / University of Newcastle / University of Bonn / Berlin / Large Geo-referenced Data Sets Vladimir Estivill-Castro Department of Computer Science & Software Engineering / J. Royal Statistical Society / Pattern Analysis and Machine Intelligence / /
Person
Optimization / Morgan Kaufmann / Torres-Vel azquez / /
Position
editor / representative / analyst / /
Product
Xtreme FS1 Headphone/Headset / /
ProvinceOrState
New York / New Mexico / California / /
PublishedMedium
IEEE Transactions on Pattern Analysis and Machine Intelligence / the Theory of Computing / Machine Learning / Theoretical Computer Science / /
Convex group clustering of large geo-referenced data sets 1 Convex Group Clustering of Large Geo-referenced Data Sets