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Reseach Article

Influence Maximization on Mobile Social Network using Location based Community Greedy Algorithm

by Smita Bhosale, Dhanshree Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 19
Year of Publication: 2015
Authors: Smita Bhosale, Dhanshree Kulkarni
10.5120/21810-5133

Smita Bhosale, Dhanshree Kulkarni . Influence Maximization on Mobile Social Network using Location based Community Greedy Algorithm. International Journal of Computer Applications. 122, 19 ( July 2015), 28-31. DOI=10.5120/21810-5133

@article{ 10.5120/21810-5133,
author = { Smita Bhosale, Dhanshree Kulkarni },
title = { Influence Maximization on Mobile Social Network using Location based Community Greedy Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 19 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number19/21810-5133/ },
doi = { 10.5120/21810-5133 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:11:27.910949+05:30
%A Smita Bhosale
%A Dhanshree Kulkarni
%T Influence Maximization on Mobile Social Network using Location based Community Greedy Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 19
%P 28-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A mobile social network plays an important role as the spread of information and influence in the form of "word-of-mouth". It is basic thing to find small set of influential people in a mobile social network such that targeting them initially. It will increase the spread of the influence . The problem of finding the most influential nodes in network is NP-hard. It has been shown that a Greedy algorithm with provable approximation guarantees can give good approximation. Community based Greedy algorithm is used for mining top-K influential nodes. It has two components: dividing the mobile social network into several communities by taking into account information diffusion and selecting communities to find influential nodes by a dynamic programming. Location Based community Greedy algorithm is used to find the influence node based on Location and consider the influence propagation within Particular area. Experiments result on real large-scale mobile social networks show that the proposed location based greedy algorithm has higher efficiency than previous community greedy algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

CGA - Community-based Greedy Algorithm LCGA – Location Based Community Greedy Algorithm