Efficient Patterns Using Hidden Web Trajectory Concept

	International Journal of P2P Network Trends and Technology (IJPTT)
	© 2013 by IJPTT Journal
	Volume-3 Issue-1
	Year of Publication : 2013
	Authors : K.Kavitha, Dr. E.Ramaraj

Citation

K.Kavitha, Dr. E.Ramaraj."Efficient Patterns Using Hidden Web Trajectory Concept". International Journal of P2P Network Trends and Technology (IJPTT), V3(1):7-11 Jan - Feb 2013, ISSN:2249-2615, www.ijpttjournal.org. Published by Seventh Sense Research Group.

Abstract

Previous Existing concepts of pattern discovery focus on background knowledge and ranking [1][2][5]. These kinds of patterns are not gives that any kind of benefits in business models. Background knowledge based patterns are contains some kinds of fake objects present it. That’s why these patterns are not show the quality. Previous existing patterns are random and rotate patterns in implementation process. Solving previous existing problems introduces the new continuous pattern with back ground and hidden web concepts. Continuous pattern works with GPS and intersection patterns [6][7]. These kinds of new patterns based results show accuracy in implementation process. This paper discusses about previous patterns to present patterns how privacy it can reaches the accuracy.

References

[1]. Atzori, Francesco Bonchi, Fosca Giannotti, Dino Pedreschi.-Anonymity Preserving Pattern Discovery, Maurizio
[2]. Longbing Cao, Li Lin, Chengqi Zhang - Domain Driven In-Depth Pattern Discovery: A practical Methodology,
[3]. Jimeng Sun Spiros Papadimitriou Christos Faloutsos - Distributed Pattern Discovery in Multiple Streams,
[4]. R.Cooley B.Mobasheer J. Srinivastava - Web Mining: Information and pattern Discovery on the World Wide Web,
[5]. Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth - Knowledge Discovery and Data Mining in Databases,
[6]. Despina Kopanaki, Nikos Pelekis, Aris Gkoulalas-Divanis, Marios Vodas Yannis Theodoridis - A Framework for Mobility Pattern Mining and Privacy-Aware Querying of Trajectory Data,

Keywords

GPS, Pattern Mining, Fake Objects, intersection patterns.