DocumentCode
3532205
Title
DiSCl: Distributed Intelligent Subspace Clustering, a density based clustering approach for very high dimensional distributed dataset
Author
Jahirabadkar, Sunita ; Kulkarni, Parag
Author_Institution
Cummins Coll. of Eng., Pune, India
fYear
2009
fDate
28-31 July 2009
Firstpage
550
Lastpage
551
Abstract
In this paper, a problem called, ldquoDistributed Subspace Clustering for high dimensional distributed database, based on density notion of clusteringrdquo is explored. To solve this problem, we described our algorithm ISC (Intelligent Subspace Clustering) which uses the concept called Hierarchical Subspace Clustering. ISC finds the input parameter epsi i.e. the distance, required for any density based clustering, adaptively at various levels of dimensionalities. This gives the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.
Keywords
deductive databases; distributed databases; learning (artificial intelligence); pattern clustering; distributed intelligent subspace clustering; hierarchical subspace clustering; high dimensional distributed database; incremental learning; Clustering algorithms; Couplings; Deductive databases; Distributed databases; Educational institutions; Testing; Cluster Density; Distributed Clustering; High dimensional data; Subspace Clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Networked Digital Technologies, 2009. NDT '09. First International Conference on
Conference_Location
Ostrava
Print_ISBN
978-1-4244-4614-8
Electronic_ISBN
978-1-4244-4615-5
Type
conf
DOI
10.1109/NDT.2009.5272086
Filename
5272086
Link To Document