Dynamic latent expertise mining in social networks

Nir Ofek, Asaf Shabtai

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


With more individuals using social networks as well as a wider range of activities available by these platforms, there is a growing need to develop knowledge-extraction methods. This article presents ExaMine, a system for identifying expertise within a user's social network connections. During the learning phase, the system mines the activities associated with each connection to generate profiles. When the user browses the Web, the system retrieves an ordered list of connections for any viewed webpage. It then uses a classification process to identify these connections as experts on the webpage's dynamic topics.

Original languageEnglish
Article number5
Pages (from-to)20-27
Number of pages8
JournalIEEE Internet Computing
Issue number5
StatePublished - 1 Jan 2014


  • data mining
  • information retrieval
  • social networks

ASJC Scopus subject areas

  • Computer Networks and Communications


Dive into the research topics of 'Dynamic latent expertise mining in social networks'. Together they form a unique fingerprint.

Cite this