CFP last date
22 April 2024
Reseach Article

Concise Query Processing in Uncertain Database

by M. Sowmya, V. Shankar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 6
Year of Publication: 2012
Authors: M. Sowmya, V. Shankar
10.5120/8571-2303

M. Sowmya, V. Shankar . Concise Query Processing in Uncertain Database. International Journal of Computer Applications. 54, 6 ( September 2012), 24-28. DOI=10.5120/8571-2303

@article{ 10.5120/8571-2303,
author = { M. Sowmya, V. Shankar },
title = { Concise Query Processing in Uncertain Database },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 6 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number6/8571-2303/ },
doi = { 10.5120/8571-2303 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:00.785124+05:30
%A M. Sowmya
%A V. Shankar
%T Concise Query Processing in Uncertain Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 6
%P 24-28
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless communication technology has been rapidly increasing, it became quite common for people to view maps or get related services from the handheld devices, such as mobile phones and PDAs. Spatial databases have witnessed an increasing number of applications recently, due to the fast advance in the fields of mobile computing and embedded systems and the spread of the Internet . Range queries are often posed by user to retrieve the useful information from a spatial database. We present a novel idea that a concise representation of a specified size for the range query results, while incurring minimal information loss, shall be computed and returned to the user. Such a concise range query not only reduces communication costs, but also offers better usability to the users, providing an opportunity for interactive exploration. The usefulness of the concise range queries is confirmed by comparing it with other possible alternatives, such as sampling and clustering. In this proposed system, we include the entities and associate the object attributes such as restaurants, shopping places etc which represents a point within a Hilbert curve which facilitates in reducing search space for spatial data, and to provide a range for attribute such that all the information is retrieved with minimal loss. The proposed system also includes peer to peer system through which multiple spatial databases can be accessed in efficient time.

References
  1. X. Lin, Y. Yuan, Q. Zhang, and Y. Zhang, "Selecting Stars: The k Most Representative Skyline Operator," Proc. Int'l Conf. Data Eng. (ICDE), 2007.
  2. C. Jermaine, S. Arumugam, A. Pol, and A. Dobra, "Scalable Approximate Query Processing with the dbo Engine," Proc. ACM SIGMOD, 2007.
  3. J. Xu, W. Wang, J. Pei, X. Wang, B. Shi, and A. W. -C. Fu, "Utility- Based Anonymization Using Local Recoding," Proc. ACMSIGKDD , 2006.
  4. H. V. Jagadish, B. C. Ooi, K. -L. Tan, C. Yu, and R. Zhang, "iDistance: An Adaptive B+-Tree Based Indexing Method for Nearest Neighbor Search," ACM Trans. Database Systems, vol. 30, no. 2, pp. 364-397, 2005.
  5. K. Mouratidis, D. Papadias, and S. Papadimitriou, "Tree-Based Partition Querying: A Methodology for Computing Medoids in Large Spatial Datasets," VLDB J. , vol. 17, no. 4, pp. 923-945, 2008.
  6. C. S. Jensen, D. Lin, B. C. Ooi, and R. Zhang, "Effective Density Queries on Continuously Moving Objects," Proc. Int'l Conf. Data Eng. (ICDE), 2006.
  7. G. Ghinita, P. Karras, P. Kalnis, and N. Mamoulis, "Fast Data Anonymization with Low Information Loss," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2007
  8. G. Aggarwal, T. Feder, K. Kenthapadi, S. Khuller, R. Panigrahy, D. Thomas, and A. Zhu, "Achieving Anonymity via Clustering," Proc. Symp. Principles of Database Systems (PODS), 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Spatial Database Range Queries