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Computing a profit-maximizing sequence of offers to agents in a social network

Publication ,  Journal Article
Bhattacharya, S; Korzhyk, D; Conitzer, V
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
December 26, 2012

Firms have ever-increasing amounts of information about possible customers available to them; furthermore, they are increasingly able to push offers to them rather than having to passively wait for a consumer to initiate contact. This opens up enormous new opportunities for intelligent marketing. In this paper, we consider the limit case in which the firm can predict consumers' preferences and relationships to each other perfectly, and has perfect control over when it makes offers to consumers. We focus on how to optimally introduce a new product into a social network of agents, when that product has significant externalities. We propose a general model to capture this problem, and prove that there is no polynomial-time approximation unless P=NP. However, in the special case where agents' relationships are symmetric and externalities are positive, we show that the problem can be solved in polynomial time. © 2012 Springer-Verlag.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

December 26, 2012

Volume

7695 LNCS

Start / End Page

482 / 488

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Bhattacharya, S., Korzhyk, D., & Conitzer, V. (2012). Computing a profit-maximizing sequence of offers to agents in a social network. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7695 LNCS, 482–488. https://doi.org/10.1007/978-3-642-35311-6_36
Bhattacharya, S., D. Korzhyk, and V. Conitzer. “Computing a profit-maximizing sequence of offers to agents in a social network.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7695 LNCS (December 26, 2012): 482–88. https://doi.org/10.1007/978-3-642-35311-6_36.
Bhattacharya S, Korzhyk D, Conitzer V. Computing a profit-maximizing sequence of offers to agents in a social network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Dec 26;7695 LNCS:482–8.
Bhattacharya, S., et al. “Computing a profit-maximizing sequence of offers to agents in a social network.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7695 LNCS, Dec. 2012, pp. 482–88. Scopus, doi:10.1007/978-3-642-35311-6_36.
Bhattacharya S, Korzhyk D, Conitzer V. Computing a profit-maximizing sequence of offers to agents in a social network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Dec 26;7695 LNCS:482–488.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

December 26, 2012

Volume

7695 LNCS

Start / End Page

482 / 488

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences