Efficient Query Service Provider using Clustering K-Nearest Neighborhood Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-36 Number-4
Year of Publication : 2016
Authors : A.Roslin Deepa, Dr. Ramalingam Sugumar
  10.14445/22312803/IJCTT-V36P132

MLA

A.Roslin Deepa, Dr. Ramalingam Sugumar "Efficient Query Service Provider using Clustering K-Nearest Neighborhood Algorithm". International Journal of Computer Trends and Technology (IJCTT) V36(4):176-182 June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Data mining has wide variety of real time application in many fields such as financial, telecommunication, biological, and among government agencies. So the query processing system is also an important thing to access and search the database. Once the KNN query service is outsourced, data confidentiality and query privacy become the important issues, because the data owner loses the control over the data. This type of queries are very useful in many applications namely decision making, data mining and pattern recognition. In this paper we studies a KNN based search which was worked on very efficiently. This method utilize a conventional data-partitioning index on the dataset, employ the state-of-the-art database techniques including k nearest neighbor (KNN) retrieval and reverse KNN search technique using Clustering find the minimum value and calculate the average using k-means algorithm. The empirical study of this paper is also providing the efficiency of the KNN based query processing on spatial databases.

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Keywords
Data mining, K-Nearest Neighborhood, Query processing, Range Query, Spatial Data base.