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Reseach Article

Efficient K-Nearest Neighbours Discovery using Complex Secure Evaluation Function in Geo Tagged Dataset

by Kommuri Manoj, B. Tarakeswara Rao
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 14
Year of Publication: 2015
Authors: Kommuri Manoj, B. Tarakeswara Rao
10.5120/ijca2015907526

Kommuri Manoj, B. Tarakeswara Rao . Efficient K-Nearest Neighbours Discovery using Complex Secure Evaluation Function in Geo Tagged Dataset. International Journal of Computer Applications. 131, 14 ( December 2015), 25-28. DOI=10.5120/ijca2015907526

@article{ 10.5120/ijca2015907526,
author = { Kommuri Manoj, B. Tarakeswara Rao },
title = { Efficient K-Nearest Neighbours Discovery using Complex Secure Evaluation Function in Geo Tagged Dataset },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 14 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number14/23518-2015907526/ },
doi = { 10.5120/ijca2015907526 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:27:22.107897+05:30
%A Kommuri Manoj
%A B. Tarakeswara Rao
%T Efficient K-Nearest Neighbours Discovery using Complex Secure Evaluation Function in Geo Tagged Dataset
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 14
%P 25-28
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The materialization of mobile equipment with fast Internet connectivity and geo-tagged capabilities has led to a revolution in personalized position-based services where clients are enabled to admittance information about points of interest that are pertinent to their interests and are also close to their geo tagged coordinates. The important type of queries that absorb location attributes is symbolized by nearest-neighbor queries, where a client wants to retrieve the k- Point of interests that are nearest to the user’s current location. Entities specialized in various areas of interest and gather large amounts of geo-tagged data that appeal to subscribed users. In this paper the proposes development and implementation of frame work to provide more complex protected evaluation method on cipher texts, like skyline queries and security protection guarantees against the client, to prevent it from learning anything other than the received k query results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

points of interest (POI) geo-tagged data Query processing and KNN Query.