DocumentCode
2924352
Title
Soft clustering from crisp clustering using granulation for mobile call mining
Author
Lingras, P. ; Nimse, S. ; Darkunde, N. ; Muley, A.
Author_Institution
Dept. of Math. & Comput. Sci., St. Mary´´s Univ., Halifax, NS, Canada
fYear
2011
fDate
8-10 Nov. 2011
Firstpage
410
Lastpage
416
Abstract
This paper builds on an earlier study for transforming clustering schemes between two levels of granularity. A crisp clustering scheme of coarse granules can be easily transferred to a crisp clustering at finer level of granularity. However, crisp clustering of finer granules cannot be easily transferred to coarser granules due to the non-overlapping nature of crisp clusters. We propose the use of soft clustering schemes, which allow for possible overlap of clusters. The clustering of finer granules given by phone calls is first transferred to fuzzy clustering and then to rough clustering. The process highlights the complementary nature of fuzzy and rough set theory.
Keywords
data mining; fuzzy set theory; pattern clustering; rough set theory; coarse granules; crisp clustering scheme; fuzzy clustering; fuzzy set theory; mobile call mining granulation; nonoverlapping nature; phone calls; rough clustering; rough set theory; soft clustering; Clustering algorithms; Data mining; Mobile communication; Mobile computing; Mobile handsets; Social network services; Upper bound; Clustering; fuzzy clustering; granular computing; k-means; mobile call mining; rough clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2011 IEEE International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-4577-0372-0
Type
conf
DOI
10.1109/GRC.2011.6122632
Filename
6122632
Link To Document