NDLI: Pattern identification using rough set clustering for spatio-temporal dataset

Content Provider	IEEE Xplore Digital Library
Author	Jayakumaran, C. Karuppanan, K.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Easwari Eng. Coll., Chennai, India (Jayakumaran, C.; Karuppanan, K.)
Abstract	Spatial temporal data mining is highly demanding because of the complexity of huge amount of data collected. Interpreting the spatial data is made easier by the process of visualizing quantitative spatial data leading to the discovery of interesting patterns. To understand the spatial structure of the data, better clustering algorithms are to be used. The purpose of this paper is to investigate the efforts of applying rough set theory onto spatial clustering. Rough set theory utilizes the spatial structure of the data resulting in better pattern identification. The results of our proposed model are compared with the hard clustering methods such as single linkage, ward's and density based clustering which proves that the rough set based soft clustering converges data points faster. Our investigation shows that the rough set based clustering helps in identifying clusters that are more cohesive compared with the hard partitioning clustering method. Soft Clustering provides more information about the structure of the data than hard clustering.
Starting Page	1598
Ending Page	1603
File Size	264418
Page Count	6
File Format	PDF
ISBN	9781479924325
e-ISBN	9781467362177
DOI	10.1109/ICACCI.2013.6637419
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis K-means Cohesion Spatial and temporal data set Regionalization Spatial databases Approximation methods Data mining Pattern identification Variance Rough set Couplings Spatial distribution Clustering algorithms Hard clustering Set theory Air pollution
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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