DocumentCode
3088905
Title
Propagation of knowledge from crisp and soft clustering through a granular hierarchy
Author
Lingras, Pawan ; Bhalchandra, P. ; Khamitkar, S. ; Mekewad, S. ; Rathod, R.
Author_Institution
St. Mary´s Univ., Halifax, NS, Canada
fYear
2012
fDate
4-7 Dec. 2012
Firstpage
6
Lastpage
11
Abstract
Information granules allow us to abstract real world objects using their relevant attributes. Level of abstraction allows us to create a network of information granules that are connected to each other through a real-world relationship. For example, the phone calls are connected to the origin and destination phone numbers. This paper describes the relationship between clustering schemes by propagating the information through the connection between granules. We focus on the hierarchical granular graphs, where phone numbers represent the higher level (coarser) granules that are connected to phone calls which are lower level (finer) granules. The paper studies the effect of transferring crisp and fuzzy clustering schemes through the granular hierarchy. The fuzzy clustering is shown to provide a better technique for such a transfer. Rough clustering derived from fuzzy clustering is shown to be a good instrument for comparing crisp and fuzzy clustering schemes.
Keywords
fuzzy set theory; granular computing; graph theory; pattern clustering; clustering schemes; crisp clustering; fuzzy clustering; granular hierarchy; hierarchical granular graphs; information granules; knowledge propagation; phone calls; phone numbers; rough clustering; soft clustering; Clustering algorithms; Data mining; Hybrid intelligent systems; Indexes; Mobile handsets; Transforms; Upper bound; Crisp; cluster quality; fuzzy clustering; granular graphs; knowledge propagation; mobile call mining; rough;
fLanguage
English
Publisher
ieee
Conference_Titel
Hybrid Intelligent Systems (HIS), 2012 12th International Conference on
Conference_Location
Pune
Print_ISBN
978-1-4673-5114-0
Type
conf
DOI
10.1109/HIS.2012.6421301
Filename
6421301
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