eCite Digital Repository

Preference Aware Influence Maximization

Citation

Jiang, C and Li, W and Bai, Q and Zhang, M, Preference Aware Influence Maximization, Multi-agent and Complex Systems: Studies in Computational Intelligence, Springer, Q Bai, F Ren, K Fujita, M Zhang and T Ito (ed), Berlin, pp. 153-164. ISBN 978-981-10-2563-1 (2016) [Research Book Chapter]

Copyright Statement

Copyright 2017 Springer Science+Business Media Singapore

DOI: doi:10.1007/978-981-10-2564-8_11

Abstract

With the development of social network, online marketing has become more popular and developed in an unprecedented scale. Viral marketing propagates influence through ‘word-of-mouth’ effect. As for development of viral marketing, it is critical to select a set of influential users in the network to propagate influence as much as possible with limited resources. In this chapter, we proposed a model called Preference-based Trust Independent Cascade Model. Based on the experimental results, the Preference-based Trust Independent Cascade Model is able to obtain better results than some traditional models. Comparing with other existing methods, such as trust-only approach and random selection approach, the proposed Preference-based Trust Independent Cascade Model considers both user preference and trust connectivity.

Item Details

Item Type:Research Book Chapter
Keywords:Influence mining, influence maximisation
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140734
Year Published:2016
Web of Science® Times Cited:2
Deposited By:Information and Communication Technology
Deposited On:2020-09-02
Last Modified:2020-10-16
Downloads:0

Repository Staff Only: item control page