Top-K Spatial Preference Query with Range Based Skyline Query in Mobile Environment
Keywords:
Spatial data mining, Skyline Query Processing, Interesting PointsAbstract
As the location based service makes the users to process their queries from anywhere and at anytime, the spatial query processing that with this provides the processing on the basics of the spatial attributes in the skyline. With thus provides the users to identify the nearest neighbour among their query given with its spatial attributes. With the existing, they have done the skyline query processing based on the range in the spatial attribute for analyzing the nearest among the other skyline data sets. They have done these using two novel algorithms as index and non index algorithm. We are going to concentrate by making with that range query to process on the basis of user�s feedback as their rating for the skyline query processing. Here the processing is done by ranking on the spatial attribute in the skyline data sets. When the user makes the feedback as their rating for the result of the skyline, this will be also analyzed while considering the next query processing for the nearest neighbour in the skyline query processing. Here, we are going to consider the algorithms as nearest neighbour algorithm and branch and bound algorithm in which this makes the analysis on the basics of both nearest and the minimum bound within the skyline.
References
S.Borzonyi, D.Kossmann, and K. Stocker, “Range based skyline queries in mobile environment” Proc. Int’l Conf. Data Eng., pp. 421-430, 2013.
S.Borzonyi, D.Kossmann, and K. Stocker, “The Skyline Operator,” Proc. Int’l Conf. Data Eng., pp. 421-430, 2001.
H. Hu and D.L. Lee, “Range Nearest Neighbor Query,” IEEE Trans. Knowledge and Data Eng., vol. 18, no. 1, pp. 78-91, Jan. 2006.
Z. Huang, H. Lu, B.C. Ooi, and K.H. Tong, “Continuous Skyline Queries for Moving Objects,” IEEE Trans. Knowledge and Data Eng.,vol. 18, no. 12, pp. 1645-1658, Dec. 2006.
Ilaria Bartolini, Paolo Ciaccia, and Marco Patella, “The Skyline of a Probabilistic Relation” IEEE Trans. on Knowledge and Data Engineering, vol. 25, no.7, July 2013.
W.S. Ku, R. Zimmermann, W.-C. Peng, and S. Shroff, “Privacy Protected Query Processing on Spatial Networks,” Proc. ICDE Workshop Privacy Data Management, pp. 215-220, 2007.
Parke Godfrey, Ryan Shipley, Jarek Gryz“Maximal Vector Computation in Large Data Sets”
D.Papadias, Y.Tao, G.Fu, B. Seeger, “An Optimal and Progressive Algorithm for Skyline Queries” Proc. ACM SIGMOD Int’l conf. management of data,2003.
D. Papadias, Y. Tao, G. Fu, and B. Seeger, “Progressive Skyline Computation in Database Systems,” ACM Trans. Database Systems, vol. 30, no. 1, pp. 41-82, 2005.
M. Sharifzadehand C. Shahabi, “The Spatial Skyline Queries,”Proc. 32nd Int’l Conf. Very Large Data Bases (VLDB), 2006.
J. Xu, X. Tang, H. Hu, and J. Du, “Privacy-Conscious Location- Based Queries in Mobile Environments,” IEEE Trans. Parallel and Distributed Systems, vol. 21, no. 3, pp. 313-326, Mar. 2010.
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