Fast Searching of Nearest Neighbor Using Key Values in Data Mining

Authors(2) :-Sri Vidhya. A, Prof. Ashwin. M

Spatial query which focus only on the geometrics properties of an object like points, rectangle etc. Now a day’s many new applications which involve the queries that completely aim to return an object which satisfy equally on spatial predicate and their associated text. Spatial query takes the given location and a keyword as the input and finds the object that matches the both spatial predicate and the text related to the given query. Some of the spatial queries are range search and nearest neighbor retrieval which includes only geometric properties of an object. For example, In case of considering all the hotels, a nearest neighbor query would find for the hotel which is near, along with menu that user required to have in hotel among all the hotels in particular location simultaneously. At present the better solution is based on IR2-Tree which as few drawbacks that affect the efficiency in query retrieval. So we develop a new method Spatial inverted index that cope with 3D data to answer the nearest neighbor query using keyword along with key values in real time. Searching nearest neighbor query using key values will result in quick response of query when compared to keyword in real time.

Authors and Affiliations

Sri Vidhya. A
Department of CSE, Adhiyamaan College of engineering, Hosur, Tamilnadu, India
Prof. Ashwin. M
Department of CSE, Adhiyamaan College of engineering, Hosur, Tamilnadu, India

Spatial Query, Nearest Neighbor Search, IR2-Tree, Key Value and Spatial inverted index

 [1] S. Agrawal, S. Chaudhuri, and G. Das. Dbxplorer: “A system for keyword  based search over relational databases. “In Proc. Of  International Conference on Data Engineering (ICDE), pages 5–16, 2002.

[2] N. Beckmann, H. Kriegel, R. Schneider, and B. Seeger. “The R*tree: An efficient and robust access method for points and rectangles.” In Proc. of ACM Management of Data (SIGMOD), pages 322–331, 1990.

[3] G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S. Sudarshan. “Keyword searching and browsing in databases using banks.” In Proc. of International Conference on Data Engineering (ICDE), pages 431–440, 2002.

[4] X. Cao, L. Chen, G. Cong, C. S. Jensen, Q. Qu, A. Skovsgaard, D. Wu, and M. L. Yiu. “Spatial keyword querying.” In ER, pages 16–29, 2012.

[5] X. Cao, G. Cong, and C. S. Jensen. “Retrieving top-k prestige-based relevant spatial web objects.”PVLDB, 3(1):373–384, 2010.

[6] X. Cao, G. Cong, C. S. Jensen, and B. C. Ooi. “Collective spatial keyword querying.” In Proc. of ACM Management of Data (SIG- MOD), pages 373–384, 2011.

[7] B. Chazelle, J. Kilian, R. Rubinfeld, and A. Tal. “The bloomier filter: an efficient data structure for static support lookup tables.”In Proc. of the Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 30–39, 2004.

[8] Y.-Y. Chen, T. Suel, and A. Markowetz. “Efficient query processing in geographic web search engines.”In Proc. Of ACM Management of Data (SIGMOD), pages 277–288, 2006.

[9] E. Chu, A. Baid, X. Chai, A. Doan, and J. Naughton. “Combining keyword search and forms for ad hoc querying of databases.” In Proc. of ACM Management of Data (SIGMOD), 2009.

[10] G. Cong, C. S. Jensen, and D. Wu. “Efficient retrieval of the top-k most relevant spatial web  objects.”PVLDB, 2(1):337–348, 2009.

[11] C. Faloutsos and S. Christodoulakis. “Signature files: An access method for documents and its analytical performance evaluation.” ACM Trans- actions on Information Systems (TOIS), 2(4):267–288, 1984.

[12] I. D. Felipe, V. Hristidis, and N. Rishe. “Keyword search on spatial databases.” In Proc. of International Conference on Data Engineering (ICDE), pages 656–665, 2008.

[13] R. Hariharan, B. Hore, C. Li, and S. Mehrotra. “Processing spatial keyword (SK) queries in geographic information retrieval (GIR) systems.” In Proc. of Scientific and Statistical Database Management (SSDBM), 2007.

[14] D. Zhang, Y.M. Chee, A. Mondal, A.K.H. Tung, and M. Kitsuregawa, “Keyword Search in Spatial Databases: Towards Searching by Document,” Proc. Int’l Conf. Data Eng. (ICDE), pp. 688-699, 2009. 

Publication Details

Published in : Volume 1 | Issue 2 | March-April 2015
Date of Publication : 2015-04-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 81-85
Manuscript Number : IJSRSET151180
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sri Vidhya. A, Prof. Ashwin. M, " Fast Searching of Nearest Neighbor Using Key Values in Data Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 2, pp.81-85, March-April-2015. Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET151180

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