id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
absel-408	Thavikulwat, Precha	Affinity Propagation: A Clustering Algorithm for Computer-Assisted Business Simulations and Experiential Exercises	2014	5	.pdf	application/pdf	3653	232	54	Affinity propagation is a graph theoretic clustering method recently developed by Frey and Dueck (2007), who have tested it against k-centers clustering, an iterative partitioning method similar to the popular k-means procedure that is available on SPSS 15, differing in that k- means clusters items around a computed central values whereas k-centers clusters them around exemplars, each one being the most central item of its cluster. When applied to a large database of human faces and a large database of mouse DNA segments, Frey and Dueck found that affinity propagation gave rise to smaller errors and arrived at its Developments in Business Simulation and Experiential Learning, Volume 35, 2008 220 mailto:pthavikulwat@towson.edu solution at least two orders of magnitude faster, an important consideration because clustering data is inherently a computationally intensive problem.	cache/absel-408.pdf	txt/absel-408.txt