Attribute based diversification of seeds for targeted influence maximization
type: Item
instance of: scholarly article
title: Attribute based diversification of seeds for targeted influence maximization
zbMATH Open document ID: 1479.91278
author: Antonio Caliò
author: Andrea Tagarelli
published in: Information Sciences
publication date: 2021-12-01T00:00:00Z
review text: This paper studies attribute based diversification of seeds for targeted influence maximization. The emphasis is on the categorical attribute-based diversity of the seeds. The problem of attribute-based diversity-sensitive targeted influence maximization is proposed. The node set is associated with a categorical dataset describing the profiles of nodes. A class of non-decreasing and sub-modular functions are designed to represent the categorical diversity. A solution to the attribute-based diversity-sensitive targeted influence maximization problem is provided under the reverse influence sampling approach. Both the diversity awareness and the targeted nature of the attribute-based diversity-sensitive targeted influence maximization problem have been tackled. Based on the triggering model, a algorithm regarding attribute-based diversity-sensitive targeted influence maximization has been proposed which gives a \(k\)-seed with certain approximation ratio with high probability. Numerical experiments have been conducted to illustrate the proposed method.
reviewed by: Yilun Shang
Mathematics Subject Classification ID: 91D30
zbMATH DE Number: 7436909
zbMATH Keywords: diversity in influence maximization
zbMATH Keywords: monotone submodular categorical set functions
zbMATH Keywords: reverse influence sampling
zbMATH Keywords: viral marketing
zbMATH Keywords: social recommendation
describes a project that uses: SIMPATH
describes a project that uses: CoFIM
MaRDI profile type: Publication
full work available at URL: j.ins.2020.08.093
OpenAlex ID: W3081775248
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cites work: C2IM: community based context-aware influence maximization in social networks
DOI: 10.1016/J.INS.2020.08.093
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description: scientific article; zbMATH DE number 7436909