NDLI: An improved design approach in spatial databases using frequent Association Rule Mining algorithm

Content Provider	IEEE Xplore Digital Library
Author	Tripathy, A. Das, S. Patra, P.K.
Copyright Year	2010
Description	Author affiliation: School of Computer Engineering, KIIT University, Bhubaneswar, INDIA (Tripathy, A.; Das, S.) \|\| Department of Computer Science & Engineering, CET, Bhubaneswar, INDIA (Patra, P.K.)
Abstract	Recently Negative Association Rule Mining (NARM) has become a focus in the field of spatial data mining. Negative association rules are useful in data analysis to identify objects that conflict with each other or that complement each other. Much effort has been devoted for developing algorithms for efficiently discovering relation between objects in space. All the traditional association rule mining algorithms were developed to find positive associations between objects. By positive correlation we refer to associations between frequently occurring objects in space such as a city is always located near a river and so on. Recently the problem of identifying negative associations (or “dissociations”) that is absence of objects has been explored and considered relevant. This paper presents an improved design approach for mining both positive and negative association rules in spatial databases. This approach extends traditional association rules to include negative association rules using a minimum support count. Experimental results show that this approach is efficient on simple and sparse datasets when minimum support is high to some degree, and it overcomes some limitations of the previous mining methods. The proposed form will extend related applications of negative association rules to a greater extent.
Starting Page	404
Ending Page	409
File Size	364239
Page Count	6
File Format	PDF
ISBN	9781424447909
DOI	10.1109/IADCC.2010.5422905
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-02-19
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Data analysis Data engineering Data Mining Spatial databases Rivers Association Rule Association rules Data mining Negative Association Rule Computer science Design engineering Cities and towns correlation coefficient
Content Type	Text
Resource Type	Article

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