eprintid: 2373
rev_number: 12
eprint_status: archive
userid: 243
dir: disk0/00/00/23/73
datestamp: 2016-12-30 08:26:32
lastmod: 2016-12-30 08:26:32
status_changed: 2016-12-30 08:26:32
type: conference_item
metadata_visibility: show
creators_name: Pham, Van Canh
creators_name: Ha, Kim Dung
creators_name: Ngo, Quang Dung
creators_name: Vu, Quang Cao
creators_name: Hoang, Xuan Huan
title: A new viral marketing strategy with the competition in the large-scale Online Social Networks
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: The problem of Influence Maximization (IM) on social networks proposed firstly by Kempe et al. (2003) has been researched and developed with many cases. However, the IM in limited time while unwanted users are restricted is still a new potential subject. In this paper, we conducted research the problem on the model of information diffusion name Locally Bounded Diffusion and tested some useful heuristic algorithms. The results of the experiment on some real datasets of social networks show that the algorithm meta-heuristic generated better output than the others.
date: 2016
date_type: published
full_text_status: public
pres_type: paper
event_title: RIVF 2016
event_type: conference
refereed: TRUE
citation:   Pham, Van Canh and Ha, Kim Dung and Ngo, Quang Dung and Vu, Quang Cao and Hoang, Xuan Huan  (2016) A new viral marketing strategy with the competition in the large-scale Online Social Networks.  In: RIVF 2016.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2373/1/CanhRIVF.pdf