Discovering cohesive subgroups from social networks for targeted advertising

Wan Shiou Yang, Jia Ben Dia

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)


In this paper, we propose a framework that utilizes the concept of a social network for the targeted advertising of products. This approach discovers the cohesive subgroups from a customer's social network as derived from the customer's interaction data, and uses them to infer the probability of a customer preferring a product category from transaction records. This information is then used to construct a targeted advertising system. We evaluate the proposed approach by using both synthetic data and real-world data. The experimental results show that our approach does well at recommending relevant products.

Original languageEnglish
Pages (from-to)2029-2038
Number of pages10
JournalExpert Systems with Applications
Issue number3
Publication statusPublished - 2008 Apr 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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