GDL

Survey on the State of Agile Practices Implementation in Pakistan

ISSN 2223-4985
Journal from gdlhub / 2017-08-14 11:52:32
Oleh : Siddhi Nath Rajan , Ashok K Sinha , J B Singh, International Journal of Information and Communication Technology Research
Dibuat : 2012-06-23, dengan 1 file

Keyword : Spatial Data Base,SDT
Subjek : Survey on the State of Agile Practices Implementation in Pakistan
Url : http://esjournals.org/journaloftechnology/archive/vol2no5/vol2no5_8.pdf
Sumber pengambilan dokumen : Internet

In the core concept of spatial data mining we need to investigate the neighbors of many objects in the single run of typical data


mining algorithm. This means that in spatial data mining algorithm we have to efficiently process the neighborhood relations. An


integration of spatial data mining algorithms and the potential of spatial database management system (SDBMS) will help efficiently


providing general concept of neighborhood relation and its implementation. If properly integrated, this will speed up the industrial


application development of spatial database and applying the traditional data mining concept on that[1][4][5][6].


Here in this paper the neighborhood relation and neighbourhood index has been discussed and the related small set of database


primitives has been defined. The proposed basic operations reduce the search space and support well the typical data mining


algorithms.


Such database primitives have been implemented on top of a commercially available Spatial Database Management System


(SDBMS) Oracle10g [6][7].

Deskripsi Alternatif :

In the core concept of spatial data mining we need to investigate the neighbors of many objects in the single run of typical data


mining algorithm. This means that in spatial data mining algorithm we have to efficiently process the neighborhood relations. An


integration of spatial data mining algorithms and the potential of spatial database management system (SDBMS) will help efficiently


providing general concept of neighborhood relation and its implementation. If properly integrated, this will speed up the industrial


application development of spatial database and applying the traditional data mining concept on that[1][4][5][6].


Here in this paper the neighborhood relation and neighbourhood index has been discussed and the related small set of database


primitives has been defined. The proposed basic operations reduce the search space and support well the typical data mining


algorithms.


Such database primitives have been implemented on top of a commercially available Spatial Database Management System


(SDBMS) Oracle10g [6][7].

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