Interaction-Aware Influence Maximization in Social Networks

Shuyang Gu (), Chuangen Gao and Weili Wu ()
Additional contact information
Shuyang Gu: The University of Texas at Dallas
Chuangen Gao: School of Computer Science and Technology, Shandong University
Weili Wu: The University of Texas at Dallas

A chapter in Nonlinear Combinatorial Optimization, 2019, pp 285-294 from Springer

Abstract: Abstract Influence maximization problem is among the most important topics in the area of social networking, it has attracted a lot of research work. Recently, the influence maximization problem has been extended to practical scenarios. In this chapter, we present one cutting-edge problem named interaction-aware influence maximization, which involves nonsubmodular optimization.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-16194-1_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030161941

DOI: 10.1007/978-3-030-16194-1_14

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().