Manuscript Number : CSEIT1833707
A Greedy Algorithm Approach for Influential Node Tracking on Dynamic Social Network
Authors(2) :-P. Maheswari, K. Jaya Krishna A mobilesocial network assumes a critical part as the spread of data and influence as "informal". It is essential thing to discover little arrangement of powerful individuals in a mobilesocial network with the end goal that focusing on them at first. It will expand the spread of the influence.The issue of finding the most powerful nodes in arranges is NP-hard. It has been demonstrated that a Greedy algorithm with provable estimate certifications can give great guess. Group based Greedy algorithm is utilized for mining top-K persuasive nodes. It has two parts: partitioning the mobilesocial network into a few groups by considering data dissemination and choosing groups to discover powerful nodes by a dynamic programming. Location Based community Greedy algorithm is utilized to discover the influencenode in view of Location and consider the influence spread inside Particular region. Examinations result on genuine expansive scale mobile informal organizations demonstrate that the proposed location based insatiable algorithm has higher effectiveness than past group greedyalgorithm.
P. Maheswari Influence maximization, Mobile social network, community greedy algorithm, and Location based community greedy algorithm. Publication Details Published in : Volume 3 | Issue 4 | March-April 2018 Article Preview
Student of MCA in ,QIS College of Engineering & Technology, Ongole, Andhra Pradesh, India
K. Jaya Krishna
Associate Professor in Dept. of MCA, QIS College of Engineering &Technology, Ongole Andhra Pradesh, India
Date of Publication : 2018-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1272-1277
Manuscript Number : CSEIT1833707
Publisher : Technoscience Academy