Applications of Frequent Pattern Mining - Frequent Pattern Mining - page 459

141. M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New Algorithms for Fast Discovery of
Association Rules. KDD Conference , pp. 283-286, 1997.
142. S. Zhang, T. Wang. Discovering Frequent Agreement Subtrees from Phylogenetic Data. IEEE
Transactions on Knowledge and Data Engineering , 20(1), pp. 68-82, 2008.
143. X. Zhang, N. Mamoulis, D. W. Cheung, Y. Shou. Fast mining of spatial collocations. ACM
KDD Conference , pp. 384-393, 2004.
144. W. Zhou, H. Liu, and H. Cheng. Mining closed episodes from event sequences efficiently,
PAKDD Conference , 2010.
145. http://fimi.ua.ac.be/.
146. http://www.kdnuggets.com/software/associations.html.
147. http://www.comp.nus.edu.sg/

∼ dm2/.

148. http://www.cs.cmu.edu/ wcohen/#sw.

149. http://www.borgelt.net//software.html
150. http://cran.at.r-project.org/web/packages/arules/index.html
151. http://www.decidyn.com/SmartBundle.php?id=91005.
152. http://www.wizsoft.com/.
153. http://www.xore.com/.
154. http://www.cs.waikato.ac.nz/ml/weka/.
155. http://adrem.ua.ac.be/

∼

goethals/software/.
156. http://www.cs.umb.edu/

∼

∼ laur/ARtool/.

157. http://cgi.csc.liv.ac.uk/ frans/KDD/Software/FPgrowth/fpGrowth.html.

158. http://www.oracle.com/technetwork/database/options/advanced-analytics/odm/index.html.
159. http://www2.sas.com/proceedings/forum2007/132-2007.pdf.
160. http://sourceforge.net/projects/ibmquestdatagen/.

∼