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  Nearest Neighbor Search with Keywords in Spatial Databases  
  Authors : Sphurti S. Sao; Dr. Rahila Sheikh
  Cite as:

 

In real world, there are billions of rows in a spatial database. If someone want to search for a location or place, it searches all the rows and return the result. Practically there can be only few rows in the database which are of importance to use. As with many pioneering solutions, the IR2-tree has a few drawbacks that affect its efficiency. The most serious issue among all is that the number of false hits can be really very large when the object of final result is far away from the query point, or the result is empty. In such cases, the query algorithm would need to load the documents of many objects, causing expensive overhead as each loading necessitates a random access. So if search is performed only in the used data subspace, the execution time would be saved. We propose such system which can implement this efficiently with the help of R-tree and Nearest neighbor algorithm using inverted Index spatial R-Tree to solve this problem.

 

Published In : IJCSN Journal Volume 5, Issue 5

Date of Publication : October 2016

Pages : 776-781

Figures :11

Tables :--

 

Sphurti S. Sao : M. Tech Student IV Sem, Dept of CSE, RCERT Chandrapur, MH, India.

Dr. Rahila Sheikh : Head of Department, Dept of CSE, RCERT Chandrapur, MH, India.

 

 

 

 

 

 

 

Nearest Neighbor Search, R-Tree, Spatial Database, Spatial Query.

The objective of our work is to increase the speed of query processing and give the real time answer of spatial query. As we have seen many applications intended for a search engine that is able to support new form of query that are combined with keyword search. The existing system does not give real time answer for such type of query. For this purpose we have proposed to use R-tree and spatial inverted index which is readily incorporable into commercial search engine that applies massive parallelism, implying its immediate industrial merits.

 

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