Algorithmic Approach for Spatial Entity and Mining

Algorithmic Approach for Spatial Entity and Mining

Priya Govindarajan, Balakrishnan R., Rajesh Kumar N.
Copyright: © 2023 |Pages: 7
DOI: 10.4018/978-1-7998-8892-5.ch021
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Abstract

Mining has gained its momentum in almost every arena of research. The mining can be either spatial or non-spatial based on the search query. For classifying or for grouping the spatial data, algorithms with extended perspectives are projected in this chapter. Besides framing algorithms, one can also provide mass points based on the required attributes as well as indexing techniques. The extended algorithms can also be manipulated for efficient and robust solution with respect to different parameters.
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Algorithmic Schema

Trouble-Free Probing (TP)

Trouble-free Probing (TP), computes the mass of every object (Algorithm 1). It uses two globalized term (assuming) Xk for manipulating the top-k results and Y calculates the value of top-k. Algorithm invokes at root node of the tree. The algorithm works recursively on the nodes of the tree, until it encounters (Sivakami & G.M.K, 2011) a terminating node. Once the non-terminating node is reached the mass M is calculated through the execution of a range of search on the tree T. The point b is ignored if its upper bound mass M+(b) can’t be greater than best-k mass Y. The term Xk and Y are overwritten when the mass M(b) is greater than Y.

  • Algorithm TP (node N) (Algorithm 1)

  • 1 For all entries in B (belongs to) N do

  • 2 If N is terminating node Then

  • 3 Take the subsidiary node N'-B

  • 4 SP (N')

  • 5 Else

  • 6 A = 1 to m do

  • 7 If M+(b) > Y Then

  • 8 Calculate M using tree T; Update M+(b)

  • 9 If M>Y Then

  • 10 Overwrite Xk (and Y) by B

Extended Branch and Bound (EBB)

While computing, Trouble-free algorithm seems to be inefficient for huge data sets. Hence a version of Extended Branch and Bound (EBB) is proposed (Algorithm 2) for accessing huge data sets. Let N be the root node of T, If N comes under the terminating category f, and then mass M(f) is manipulated. With the aid of mass for the component Mc(f) one can drive the M+(f), an upper bound of M(f). If M+(f)<=Y, (Thakoor N. et.al., 2008) then one cannot fetch best result with the sub-tree of f than those in Xk and removed from Z(subset of T).To fetch high mass, M(f) is sorted in descending order then the nodes of the subsidiary are called recursively by the entries in Z. Xk of top-k results (You wan, et.al., 2008) are updated by manipulating the mass of all N simultaneously. Whenever EBB is called recursively the globalised variables Xk and Y are updated then and there.

The vital design is to manipulate the terminating entries f in the tree T (Man Lung Yiu, et.al., 2011). If the higher bound M(f) <= Y, then there is no need to access the sub-tree T, by which the numerous mass computations can be saved.

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