Open Access System for Information Sharing

Login Library

 

Article
Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Scalable and parallelizable influence maximization with Random Walk Ranking and Rank Merge Pruning

Title
Scalable and parallelizable influence maximization with Random Walk Ranking and Rank Merge Pruning
Authors
Seungkeol KimDongeun KimJinoh OhJeong-Hyon HwangHAN, WOOK SHINWei ChenHwanjo Yu
POSTECH Authors
HAN, WOOK SHINHwanjo Yu
Date Issued
Nov-2017
Publisher
Elsevier
Abstract
As social networking services become a large part of modern life, interest in applications using social networks has rapidly increased. One interesting application is viral marketing, which can be formulated in graph theory as the influence maximization problem. Specifically, the goal of the influence maximization problem is to find a set of k nodes(corresponding to individuals in social network) whose influence spread is maximum. Several methods have been proposed to tackle this problem but to select the k most influential nodes, they suffer from the high computational cost of approximating the influence spread of every individual node.
As social networking services become a large part of modern life, interest in applications using social networks has rapidly increased. One interesting application is viral marketing, which can be formulated in graph theory as the influence maximization problem. Specifically, the goal of the influence maximization problem is to find a set of k nodes(corresponding to individuals in social network) whose influence spread is maximum. Several methods have been proposed to tackle this problem but to select the k most influential nodes, they suffer from the high computational cost of approximating the influence spread of every individual node.
URI
http://oasis.postech.ac.kr/handle/2014.oak/38973
DOI
10.1016/J.INS.2017.06.018
ISSN
0020-0255
Article Type
Article
Citation
Information Sciences, vol. 415-416, page. 171 - 189, 2017-11
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

 YU, HWANJO
Dept of Computer Science & Enginrg
Read more

Altmetric

Views & Downloads

Browse