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World Wide Web

, Volume 18, Issue 3, pp 661–679 | Cite as

Ranked content advertising in online social networks

  • Weixiong Rao
  • Lei Chen
  • Ilaria Bartolini
Article

Abstract

Online social networks (OSNs) such as Twitter, Digg and Facebook have become popular. Users post news, photos and videos, etc. and followers of such users then view and comment the posted information. In general, we call the users who produce the information as the information producers, and the users who view the information as the information consumers. The recently popular targeted information advertising systems enable the producers to target users (i.e., consumers). A key problem of the advertising system is to efficiently find the top-k most desirable targeted users, who next will view the advertised information and perform potential e-commerce activities. Unfortunately, state-of-the-art solutions to find the top-k desirable targeted users in large OSNs incur high space cost and slow running time. In this paper, we focus on designing efficient algorithms to overcome such efficiency issues. Experimental results, over synthetic and real data sets, demonstrate the effectiveness and efficiency of our algorithms.

Keywords

Top-k query Shortest path distance Efficiency 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringThe Hong Kong University of Science and TechnologyKowloonChina
  2. 2.Department of Computer Science and EngineeringUniversity of BolognaBolognaItaly

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