To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org

1. GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
Approximate Shortest Distance Computing A Query-
Dependent Local Landmark Scheme
ABSTRACT:
In this paper, we analyze the factors that affect the accuracy of distance estimation in
landmark embedding. In particular, we find that a globally selected, query independent
landmark set may introduce a large relative error, especially for nearby query nodes.
We propose a query-dependent local landmark scheme, which identifies a local landmark
close to both query nodes and provides more accurate distance estimation than the
traditional global landmark approach.
We propose efficient local landmark indexing and retrieval techniques, which achieve low
offline indexing complexity and online query complexity. Two optimization techniques on
graph compression and graph online search are also proposed, with the goal of further
reducing index size and improving query accuracy.
Furthermore, the challenge of immense graphs whose index may not fit in the memory
leads us to store the embedding in relational database, so that a query of the local
landmark scheme can be expressed with relational operators. Effective indexing and query
optimization mechanisms are designed in this context.

2. Our experimental results on large-scale social networks and road networks demonstrate
that the local landmark scheme reduces the shortest distance estimation error significantly
when compared with global landmark embedding and the state-of-the-art sketch-based
embedding.
Existing System
we analyze the factors that affect the accuracy of distance estimation in landmark
embedding. In particular, we find that a globally selected, query independent landmark set
may introduce a large relative error, especially for nearby query nodes.
Proposed system
We propose a query-dependent local landmark scheme, which identifies a local landmark
close to both query nodes and provides more accurate distance estimation than the
traditional global landmark approach.
We propose efficient local landmark indexing and retrieval techniques, which achieve low
offline indexing complexity and online query complexity. Two optimization techniques on
graph compression and graph online search are also proposed, with the goal of further
reducing index size and improving query accuracy.
System Configuration:-
Hardware Configuration:-
 Processor - Pentium –IV
 Speed - 1.1 Ghz
 RAM - 256 MB(min)

3.  Hard Disk - 20 GB
 Key Board - Standard Windows Keyboard
 Mouse - Two or Three Button Mouse
 Monitor - SVGA
Software Configuration:-
 Operating System : Windows XP
 Programming Language : JAVA
 Java Version : JDK 1.6 & above.